Making the value of technology clear
How far can large enterprises go in consolidating their software stack from IIoT and data foundations to apps? Could a startup EV OEM run its business on just two pieces of software? Fuuz, by MFGx, aims to answer that second question with a yes, using just Fuuz and Oracle NetSuite. We recently had an update briefing with Fuuz, and their focus has changed since our last conversation. They don’t fit neatly into a category and are calling what they do an industrial intelligence platform. Fuuz includes IIoT, a comprehensive data stack, no-code/low-code rapid application development tools, and MES, WMS, APS, Quality, CMMS, as well as Production and Process Monitoring solutions.
Fuuz initially aimed its platform and applications offering at small and medium businesses (SMBs) who wanted to extend their ERP to the shop floor. It still serves many SMBs with greenfield operations; however, they discovered that manufacturers with over $300 million in revenue are more mature. Their experience typically means they have a deeper understanding of why the combination of IIoT, a modern full-stack data management platform, and Purdue Model or ISA95 Level 3 applications can deliver immediate and lasting benefits.
The Fuuz platform is within multi-tenant SaaS, where each customer has their own segmented resources and database. This delivers cloud benefits while also accommodating highly regulated industries. Its Gateway enables edge connection for devices such as industrial controls, printers, scales, and CMMs, as well as edge computing. The Fuuz team claims to be winning against OT software players, IT data platform players, and manufacturing IT application powerhouses.
Many larger companies have been attempting to build out their architecture for years. One Fuuz customer is planning to replace 12 different software products with one. Some of the recent customer announcements include large and startup companies in pet food (planning to replace eight applications), EVs, auto parts, aviation, and life sciences.
Fuuz offers consolidation at many levels.
Tailor UIs, Workflows, and Apps – The Fuuz Platform offers tools, including a responsive UI builder, a workflow builder, and its own apps, as well as low-code app-building capabilities. A key differentiator is that they built these tools to address the scaling challenges of low-code/no-code solutions, implementing them as an SI before shifting entirely to a software company.
Unified Data Ontology – Each customer can select whether to use ISA95 or another structure for their enterprise data. The ontology is based on a no-code MongoDB and can span the entire enterprise.
AI Tools – The Fuuz team has decided not to build AI into the system. Customers can use its GraphQL APIs, data flows, and native MCP cloud or edge capabilities to integrate with any LLMs or AI tools they choose.
High-Value Starting Points – Since the platform encompasses everything an app needs, companies can start with their high-priority applications and obtain the entire infrastructure required for them to function. This is in stark contrast to many enterprise infrastructure approaches, which can require years before the high-value applications work well.
Fuuz’s strategy to sell and implement through partners remains strong. The ecosystem is growing, and partners have substantial control over the IP they put out on the Fuuz marketplace.
Partners have traditionally included ERP companies and their service partners. These include NetSuite, PwC, CohnReznick, Strategic Information Group, Western Computer, and Guidepath Consulting. Other partners are from IIoT, OT, or PLM backgrounds, such as Razorleaf Corporation, Castor Engineering, and newly-launched Abelara. Some have used the Fuuz platform to build their own MES, WMS, and EDI applications. Recently, Fanuc Robotics America Inc has started building Fuuz into its products to enable remote monitoring and predictive maintenance.
Fuuz’s partners often have deep and lasting relationships with customers. The partner vetting process is rigorous, ensuring that partner solution architects can help companies envision their future digital support. The goal is to grow with customers through these strong partner relationships.
Fuuz built to a vision a decade ago that few others had. At the core of the platform are flexible, modern, scalable technologies. They continue to improve, but are not flitting from one new technology trend to the next. They are building out from the original vision in a versionless approach, where upgrades never entail downtime, and customer implementations continue to support evolution.
Thank you, Craig Scott, Brad Hafer, and Steve Modrall, for briefing us on the state of the Fuuz and where Fuuz is igniting value.
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How mature is your digital approach to manufacturing operations? What are the next steps you need to take on your journey to improve digital support for the plant floor and support teams? Take our Manufacturing Operations Digital Maturity Assessment to find out.
The assessment leverages our research to assess your company’s digitalization progress in manufacturing operations. What could you do to build out from where you have already invested and succeeded? How are Top Performers doing things differently?
The assessment asks about your top objectives and challenges. It also considers five pillars of manufacturing operations digital maturity.
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How can manufacturers gain the data connectivity, analytics, and AI capabilities necessary to make informed decisions with confidence? Arch Systems was founded to provide that, and it continues to accelerate customer success via, in their words, “Intelligent Actions for Manufacturing”. Arch customers are finding that building their own AI infrastructure does not make sense when they can purchase this pre-built architecture, which includes connectors, dashboarding, a knowledge graph for context, analytics, and AI capabilities. We are excited about the progress they have made since our first briefing in the summer of 2024.
Why is managing CAD/CAM important to job shops? How does poor manufacturing data management negatively impact job shop performance and profits? More importantly, what lessons learned can they from managing product data to add control without burdening already busy resources?
Read the full report here, or download the full PDF, courtesy of Siemens.
You can also learn more from Siemens Digital Industries Software here. Thank you Siemens for supporting our work and helping us educate manufacturers on the value of improving CAD/CAM data management.
Design and production data are intrinsically related, and the data created by the shop should be managed in the context of the customer's CAD design. Unfortunately, job shops don't always manage this data and data relationships well because they don't want to be slowed down by cumbersome enterprise data management solutions. Some may not even have IT departments or the resources to implement formal data management solutions like PDM or PLM. This leads to disconnected data that is difficult to find and nearly impossible to manage as changes are received.
Unmanaged CAD/CAM Costs the Shop
Despite the challenges adopting data management, unmanaged CAD/CAM data causes frustration and reduces productivity. Our research on non-value-added time shares that technical resources only spend about one-half of their time on technical work on a typical project. They spend 19% of their time, about one day a week, on non-value-added (NVA) data management tasks such as finding information, working with the wrong data, recreating data, translating formats, and other common time wasters.1
Unmanaged CAD/CAM hurts a job shop's performance and profitability in four ways:
Four Ways to Improve
Now that we've discussed how poor data management negatively impacts job shops let's talk about how to fix it. Few job shop leaders would disagree that they should have effective control over their data, be able to reuse existing work, and capture learnings to continuously improve and avoid repeating mistakes. These factors are important to running an efficient, profitable shop. However, they can't always achieve the control they need over their CAD/CAM data because of the potential overhead of data management solutions.
In this eBook, we'll discuss four ways to increase profitability, performance, and customer satisfaction with minimal disruption and investment by taking a lightweight data management approach that manages CAD and related data like NC programs and CAM project files so they can:
Control, Access, and Share Data
Tech-Clarity's research shows that engineering and manufacturing teams must put three key capabilities in place to reduce wasted, non-value-added work. These basic capabilities include effectively controlling, accessing, and sharing information (see details on page "Control, Access, and Share with PDM").
PDM is a critical enabler to centralize and manage CAD/CAM and other related manufacturing data. It's proven to enable job shops to control, access, and share information effectively. PDM centralizes data to limit the time wasted on non-value-added tasks. It ensures that data stays current and updated, so there is no need to question or recreate work. It also allows other technical resources to have easier access to needed CAD/CAM or other data in a self-service model so they don't have to interrupt others who have their own jobs to do. Lastly, without PDM, CAM and other manufacturing data are not managed, and it is likely recreated every time a job comes in, instead of reusing NC data when the CAD is the same revision or using the manufacturing as a starting point if only minor details have changed.
Beyond internal value, customers may be more inclined to work with tech-savvy partners who can deliver more data and data-driven insights. Customers may value this information to train their own AI or improve their design process. On the other hand, job shops that are not leveraging AI have the potential to be perceived as outdated or less capable. Beyond AI, better managing CAD/CAM data sets the foundation for broader PLM capabilities. Our data shows that PDM / PLM improves operational control leading to reduced cost and higher profitability. However, the most important step is to get started by controlling, accessing, and sharing CAD/CAM data with PDM.
Build a Foundation for Future Value
Effective CAD/CAM data management is a core capability that drives agility and operational excellence internally. It also sets the stage for higher value and positive customer perception. One thing is sure, if AI does become a necessity, companies will want to have their CAD and manufacturing data in order so that AI can learn from it and leverage it. And if customers begin demanding PDM or PLM capabilities, you will have the foundation in place to support them. Mature CAD/CAM data management prepares the shop to answer questions about what they're doing about AI and PLM – internally and externally.
Put the Basics in Place
Job shops need to control, access, and share their CAD/CAM and related manufacturing data in context in order to drive agility and operational excellence, but it does not have to be burdensome and require deep IT resources. Job shops that are concerned about the overhead of managing CAD/CAM should consider a lightweight data management solution that keeps all data in a centralized location, contextualizes it, protects it, and allows people to securely collaborate on it. Today, job shops can implement basic PDM capabilities by taking a simpler, less burdensome approach. At the same time, they can leverage a solution that can scale with their needs over time.
Leverage the Cloud
Job shops looking for a lightweight PDM data management solution to manage CAD/CAM data should look to the cloud. Cloud solutions are more accessible than ever. They offer a low-cost option and reduce adoption barriers for small job shops. The path doesn't have to be burdensome. An overwhelming 78% of respondents who characterized their PLM implementation as 'Easy' had deployed a cloud-based solution compared to only 15% with onsite implementations.
Additionally, cloud solutions make it easier to securely collaborate with customers, both internally and externally. In fact, our research shows that the cloud provides value in several different ways:
What do pharmaceutical manufacturers most need? To be compliant with government regulations without wasting time and effort. Leucine set out to deliver that with its SaaS software suite, which includes hubs for Manufacturing, Quality, and, most recently, Laboratory, with Intelligence (including AI) serving it all. The company launched in 2019 and joined forces with Ecolab to sell in the US and Europe in 2022. In late 2023, Ecolab, an established cleaning and contamination control provider in the pharmaceutical industry with a digital arm, invested in Leucine.
Leucine is determined to stay focused on manufacturing and quality software for pharmaceutical companies. They aim to help customers achieve two goals:
That may sound straightforward. Yet, as they point out, most processes are inherently multidisciplinary, so the Leucine suite includes functions for manufacturing, quality, and quality lab activities. On top of the specific functional hubs sits the Intelligence Hub for dashboards, natural language Q&A based on GenAI, alerts, and insights. The Cortex Command Center includes GenAI for goal-based analytics and is typically used by process engineers, production supervisors and operational excellence professionals. Beneath is a common platform to ensure data is shared and in full context across all disciplines.
In the Manufacturing Hub, where our briefing focused, Leucine’s MES includes:
Any of these elements can be the starting point for a customer, and as they add functional elements, they seamlessly integrate with in-context data from the ontology. They assert that both data and context are dynamic and took on the challenge of that path to evolution and growth, as well as openness and connectivity.
The MES is designed for operators to have minimal friction. It includes hands-free voice-guided workflows, IoT-connected Andon light integration for process-ready signals, and proactive voice and visual alerts. This includes task timers and audible and visible escalation cues.
SaaS, with 99.9% uptime plus ongoing upgrades and security capabilities that the cloud offers, is just the start for agility and data flow. This platform has SOC 2 Type 2 Certified data security for privacy, availability, and security. Both Leucine and Ecolab have specialized expertise in FDA-ready audits, software validation and 21 CFR Part 11.
The platform streamlines connecting to varied data sources. It includes enterprise connectors with OPC-UA and SQL, APIs to QMS and LIMS, RFC and FTP to level 2 systems such as data historians, and OPC-UA or MQTT for analytical balances, plus the native logbooks in the system.
From the company’s inception, they developed a Leucine Ontology or single data model for the enterprise. This ontology has a semantic understanding of the objects involved in pharma manufacturing and quality. Increasingly, we find that an ontology is crucial to effective deployment, integration, and long-term value from manufacturing software.
One thing that stood out to us is the company’s inclusion of an FDA Tracker. This tool keeps up to date with the definition of compliance as it changes. Of course, the analytics intelligence hub and Cortex also support continuous improvement and agility.
Leucine is a US registered company and has already signed up a strong customer base worldwide since its inception six years ago. It claims over 350 GMP sites and nearly 50 pharmaceutical enterprise customers.
Ecolab brings 30 years of digital innovation, 1,400 employees in the digital group, 100,000 connected sites across 40 industries, 1,000,000 connected devices, and over 120 billion data points go through the Ecolab cloud platform every year.
We think Leucine was brilliant to bring in a strong partner as its channel to market. Ecolab has been making its mark in pharmaceuticals for years, and the decontamination and cleaning processes are a clear part of compliant manufacturing and quality.
Thank you to Leucine co-founder and CEO Vivek Gera, plus Ecolab’s Michael Cates, William Goodman, and Sarah Otterstetter for briefing Rick Franzosa and Julie Fraser on this modern approach to pharmaceutical industry production, quality, and compliance.
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How can small and mid-size businesses (SMBs) - specifically manufacturers and warehouses - gain an operations digital thread that connects from materials movement through production and quality? Ideally, with well-integrated, easy-to-deploy software. Alpiconn has been delivering a combination of MES, WMS, CMMS, QMS, and traceability for the past decade. By focusing on practicality, flexibility, and depth, this company has served various companies from its headquarters in Athens, Greece. They are now ready to expand into the rest of Europe.
Alpiconn enables a digital thread from production to quality to traceability, including the warehouse. The company started in 2008 and was rebranded as Alpiconn in 2014, so it has been building for over a decade. The Plantecho digital operations management system has four major components: MES, WMS, QC, and CMMS. From the beginning, the company’s vision was based on ISA-95. It includes all major elements of the Purdue Model’s Level 3 for seamless data flows. This end-to-end functionality is designed for small and midsize manufacturers to adopt as a digital transformation accelerator.
Plantecho is also hardware and ERP agnostic, aiming to integrate with existing systems. Minimizing the integration headache can accelerate value and enable smaller companies to adopt such a comprehensive software suite. Plantecho is designed to be a unified system that orchestrates all operations. They believe their job is to connect people, data, and processes in a way that turns complexity into clarity and sound decisions. The company has won numerous Greek awards for software, IoT, science in business, and services over the years, and seems to have loyal customers.
To serve small and mid-size businesses (SMBs), Alpiconn says this system can go live in weeks, not quarters or years. They have also focused on making the system easy to use.
Alpiconn’s focus on smaller companies began to make advanced industrial technologies accessible and practical for companies that may not have the IT capacity or know-how to implement them on their own. By doing so, Alpiconn helps modernize and elevate SME operations by applying best practices and proven tools..
They have deployed Plantecho across a wide range of industries, including chemicals, aluminum and other construction materials, as well as food and beverages of many types. The foundational structures can work with any industry due to the ISA-95 basis.
However, Plantecho can serve larger multi-plant enterprises. Its multi-tenant (not cloud) approach can support multiple plants and partners. Customers have started small and grown, some using the system for over 10 years. Customer growth has also driven new capabilities and functionality in the software.
Another key factor is that Alpiconn is a turnkey provider. They enter into long-term partnerships with customers, delivering software, services, and hardware. They tend to become trusted advisors, helping customers model and optimize their business, both initially and as things change. Alpiconn also provides ongoing consulting and support services tailored to each customer’s evolving operational needs.
In addition to the broad Plantecho digital operations management system, Alpiconn offers Flexus, a low-code, event-based data and process automation platform. Customers can use Flexus to build custom workflows and business logic to respond to situations. This flexible tool has been used to develop:
Through technology partners, Alpiconn also offers connected industrial labelling from Loftware and AR-powered indoor navigation and guidance from Insider Navigation. Alpiconn is also an Independent Software Vendor (ISV) and Machine Vision partner of Zebra Technologies, integrating industrial-grade scanning, coding, labeling, and vision solutions into its systems for full visibility and control across shop floor operations. Alpiconn also has integration partners for more complex or specialized projects, such as robotic warehouses.
The software is already available in English, and the company plans to expand more aggressively into the rest of Europe soon. Alpiconn regularly introduces major releases of Plantecho that include improvements and new features. It is exploring working with companies; this is logical, given its background in chemicals and regulated food and beverage.
AI is on the roadmap, but Alpiconn management is being conservative, ensuring they introduce AI solutions that address specific customer problems. SMBs typically balk at new technology that does not deliver clear business value.
Thank you, Theodore Papadopoulos and Athina Fysekidou, for explaining Alpiconn’s business and offerings to us. We look forward to following your expansion into the rest of Europe.
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Is your approach to product development helping you compete or holding you back?
Product development teams today face growing pressure to respond to market volatility, supply chain disruptions, and global competition. At the same time, they’re dealing with long-standing challenges like manual inefficiencies, poor collaboration, disconnected systems, and workforce shortages. These issues cause costly delays, especially during engineering-to-manufacturing hand-offs. In the past, these inefficiencies were tolerated. But today’s market demands more agility, and the tools to support it are finally available. Advances in digitalization, simulation, and AI are helping teams move faster and smarter. These issues are shaping product development.
The research identifies seven trends that are reshaping product development as companies confront this new reality. Top Performers are leading the way in adapting to these trends to gain a competitive edge. What are they doing differently, and what can others learn?
This study is based on a survey of 233 professionals involved in product development across design, engineering, and manufacturing roles. The findings reveal the biggest challenges teams face today, the trends driving change, and the strategic moves Top Performers are making to reduce risk, accelerate innovation, and deliver better products faster.
Please enjoy the summary* below. For the full research, please visit our sponsor Dassault Systèmes SOLIDWORKS (registration required).
State of Product Development
Product development continues to face an era defined by growing complexity, shrinking margins for error, and accelerating market demands. This is exacerbated as companies are under increasingly pressure not only from traditional competitors, but also from nimble startups, vertically integrated disruptors, and offshore manufacturers. At the same time, they must manage ongoing supply chain volatility, shifting customer expectations, and a growing need for smarter, more connected products.
To remain competitive, companies must design faster, adapt to change more easily, and eliminate costly inefficiencies. Yet many are still burdened by manual tasks, disconnected tools, and poor collaboration, especially between engineering and manufacturing. These challenges are not just frustrating for employees; they lead to missed deadlines, higher costs, and compromised quality. In fact, 78% of respondents report increased manufacturing and development costs due to product development challenges.
Key Findings
Top Performers, companies that consistently meet or exceed product development goals, are leading the way. Compared to Others, they are:
Expand simulation usage: Use simulation earlier and across more roles to cut physical prototyping, identify issues sooner, and improve design quality. Seventy-four percent of Top Performers use simulation to optimize performance.
How can MedTech companies accelerate digital transformation?
On Thursday, October 23 at 10:00 am EDT, please join Tech-Clarity’s Michelle Boucher for an interactive discussion with Christian Vogelei of Fresenius Medical Care and René Zoelfl of PTC as they discuss this.
They will explore topics like:
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can companies managing capital-intensive projects, such as factories, nuclear facilities, offshore platforms, rail infrastructure, and data centers, avoid delays and cost overruns? What leads to successful projects?
Significant growth is expected in the number of capital-intensive projects over the next few years. However, many of these projects will face delays, cost overruns, and execution inefficiencies. In today's climate of economic volatility, labor shortages, and complex regulations, the pressure to complete projects on time and within budget has never been higher. Still, some companies consistently outperform their competitors. What are they doing differently?
This research study explores project management strategies using a survey of 201 professionals working on capital-intensive projects. The study identifies the primary challenges companies face when managing these projects, including the underlying causes of delays and cost overruns. The findings highlight three key strategies that Top Performers use to manage risk, enhance predictability, and achieve better outcomes in today’s most complex and high-stakes projects.
Please enjoy the summary* below. For the full research, please visit our sponsor, Dassault Systèmes (registration required).
Capital-Intensive Project Challenges
Capital-intensive projects represent some of the most complex and costly initiatives a business can undertake. As global economic volatility, supply chain disruption, skilled labor shortages, and other uncertainties continue to intensify, organizations must figure out how to deliver these on time, more predictably, and with greater financial control.
The research reveals that while there is a strong need for these capital-intensive projects, their execution continues to be hindered by outdated processes, fragmented tools, and collaboration breakdowns. An overwhelming 75% of respondents report that siloed information and miscommunication have a major or significant negative impact on project success.
Overcoming Challenges
To overcome these challenges, skilled labor shortages, and financial risk, companies are investing in capabilities to improve project predictability, increase on-time completion, strengthen regulatory compliance, and become more agile in response to market shifts.
Best Practices
The research revealed three strategies that Top Performers, the most successful companies, implement to manage capital-intensive projects more effectively:
Regulatory Compliance
Evolving regulations, especially in energy, infrastructure, and life sciences, often cause delays and rework. Teams must monitor changes, document compliance, and respond to audits. Yet fragmented tools and siloed data make this a time-consuming, manual task.
Without accurate, traceable data, it’s difficult to:
Too Many Disconnected Tools
Establishing a single source of truth is the most common strategy among Top Performers for improving capital-intensive project performance. This creates a centralized repository of project data accessible to all stakeholders. While most companies recognize the value of this approach, many struggle to implement it. Respondents report widespread reliance on multiple disconnected tools, creating fragmented data environments that hinder coordination, transparency, and decision making.
On average, respondents use 7.5 standalone tools to manage project data, with 46% relying on more than eight. These include spreadsheets and general tools for managing projects, collaboration, scheduling, supply chains, risk, costing, and more.
While each tool may be well-suited for its task, many disconnected solutions make it extremely difficult to get a consolidated view of project information. Respondents report spending an average of 4.8 hours preparing for a single status meeting, while 33% say it takes six or more hours just to gather needed information.
Another issue is that data stored in multiple locations can easily become outdated or conflicting, eroding trust in its accuracy. Team members then waste time searching for and validating data.
An Integrated Platform
These challenges are driving a strong preference for integrated solutions over many disconnected, best-of-breed tools. An overwhelming 85% realize significant benefits with an integrated platform. By consolidating data and workflows, companies can reduce the risk of errors, rework, and delays while increasing transparency for executives and stakeholders. This leads to improved data accuracy, faster decision making, clear audit trails, and more optimized resource allocation. Together, these advantages translate into measurable business value (see graphic).
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full research, please visit our sponsor, Dassault Systèmes.
If you have difficulty obtaining a copy of the research, please contact us.
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Can manufacturers gain an effective digital twin capability spanning from product concept to supply chain, production process, production execution, factory automation, and controls? Dassault Systèmes believes it can deliver that today. Their UNIV+RSES vision expanded deep into the plant floor with their July acquisition of Ascon’s Qube technology and team. This new edge-to-cloud platform complements the other rich elements of DELMIA’s digital manufacturing and manufacturing operations management software offering.
This recent technology acquisition extends Dassault Systèmes' capabilities to replicate the real world in virtual form, all the way into equipment controls and automation. Dassault Systèmes has an extensive software portfolio to create digital twins of reality. The company grew initially as a product design and development leader, and the DELMIA brand has long focused on production and supply chain operations connecting the virtual and real worlds.
With the addition of Ascon technology, DELMIA aims to deliver software-defined production systems to improve highly automated manufacturing environments. Not just modeling, but replacing, vendor-specific programming of programmable logic controllers (PLCs) at level 2 of the Purdue model, would be a breakthrough. Challenges at the automation layer are many and cause huge costs and inefficiencies for large, highly automated manufacturers.
Vendor lock-in at the automation layer with proprietary hardware, software, and data formats is nearly universal. Initiatives like the Open Process Automation Forum (OPAF) are striving to break the lock; adding this virtual approach could accelerate the progress. Due to the low level of interoperability, the real-time data from these OT systems often cannot be easily accessed by the plant IT systems, such as MES. This harms decision-making speed and effectiveness. The DELMIA team rightly points out that automation setup is labor-intensive and often lacks efficiency and insights. This new technology will help alleviate these issues.
Based on early experience in automotive, DELMIA expects significant benefits for customers. Major areas include expanding transparency, improving agility to respond to changes on the shop floor, reducing line changeover and new product introduction time. They cite 30-50% reductions in line-level operating cost, changeover and downtime, to name a few.
Batch process industries may be interested in the Virtual Twin of the Plant as a Service offering. In process industries, the production process determines the product, so this process twin is a foundation for quality, yield, costs and sustainability. Without the manufacturer needing to buy software, train people and create a digital twin of a plant, DELMIA will do it for them.
This process digital twin supports tech transfer in batch process industries as well. Moving from the R&D lab (where Dassault Systèmes’ BIOVIA brand is strong) to production typically presents significant challenges to optimize equipment, processes and people. As life sciences companies also create combination devices, R&D may encompass active ingredients, process development, hardware and software. All these ideally feed into a coherent package for tech transfer into scaled-up production.
And then there’s recipe management – not just developing, but managing recipes on an enterprise basis is an enormous challenge. Following the ISA88 transformation models is a start, but few have the software to enable those transformations from R&D formula to general recipe to site recipe to master recipe to control recipe. Using the 3DEXPERIENCE® platform on the cloud with an array of applications, DELMIA hopes to deliver improved efficiency and consistency to biopharma, pharmaceutical, and CPG customers.
While the Ascon technology acquisition focuses on core complex discrete industries and the tech transfer and recipe management on batch industries, these are not DELMIA's full spectrum of customers. The DELMIA Apriso MES/MOM continues to win large multi-site deals across a wide array of industries.
They mentioned wins as a battery manufacturer, life sciences, metals and A&D companies. One was a win-back from another MES provider who got the first plant up but could not scale cost-effectively to other sites. The DELMIA Apriso multi-site advantage comes from a longstanding (at least 20 years) focus on enterprise deals and fine-tuning their rollout capabilities.
Dassault Systèmes’ 3D UNIV+RSES vision focuses not only on modeling or simulating the real world but also on generating it. (See Jim Brown’s insight from the Dassault Systèmes analyst event for more on this concept.) Now, the ability to mirror and generate new products stretches from R&D through supply chain, manufacturing and digital automated controls.
Thank you, Eric Green, Michael Bradford, and Tom Muth, for the update briefing. We have watched the DELMIA portfolio grow, improve and be merged into the greater Dassault Systèmes solution set and we look forward to watching as more of the vision comes into reality.
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What if MES were fully natively integrated into an end-to-end suite across the product and production lifecycle? For years, industry analysts have remarked that Siemens had acquired all the pieces—if only they could put them together. We recently had a briefing that focused on the MES, Opcenter, and the progress made toward the end-to-end goal:
Siemens is moving toward this goal, leveraging capabilities such as their low-code application development environment (Mendix) and their Siemens Xcelerator digital business portfolio in conjunction with Opcenter. Another advantage is Siemens's 175+ year history as a manufacturer, including 200+ factories of its own today. A manufacturing environment that Siemens Digital Industries Software can leverage as an ‘in-house laboratory’ for testing and evaluating their software solutions, including AI innovations, as well as the automation hardware assets provided by Siemens Digital Industries.
New this year is Opcenter X, combining MES, quality execution, scheduling, and LIMS on a new common cloud-native Opcenter platform.
The Opcenter brand was created in 2019 as an umbrella over several acquired/developed software products under the heading of MES/MOM. Initial development started with the user interface and data hub, allowing Siemens to market product sets for specific manufacturing industries. These early options used different underlying MES systems depending on the vertical industry.
In parallel, Siemens began the long and arduous process of creating a common platform, aided by some key technologies that they had available. The Opcenter Execution platform is moving rapidly from their two heritage MES products to a single modular, scalable, cloud native infrastructure with a lower TCO than traditional MES solutions.
We recall discussing the long-range plan with Siemens in 2023, where this migration from multiple applications to a single modular infrastructure was planned to be completed in 4 years. Now we are seeing the initial deliveries on this platform in 2025. Over the next two years, Siemens intends to deliver functionality for the remaining supported industries.
Companies, especially small and medium-sized manufacturers, need a more cost-compelling approach to MES. The total cost of ownership is more than the cost of the software. Other considerations include the time and expense of implementation, including configuration, training, and integration. Siemens has addressed these cost challenges in several ways:
Siemens announced Teamcenter Service Lifecycle Management 2-3 years ago, and it is now becoming a cornerstone of their strategy for the Aerospace and Defense (A&D) market, while also serving multiple industries. As reported by Tech-Clarity in “Siemens Support for SLM Exceeded Our Expectations”, the combination of this SLM capability as part of the Siemens Xcelerator portfolio fills in key artifacts to the digital thread, enabling full lifecycle support from product design through services.
From an Opcenter perspective, they are betting on the assumption that service plan execution contains many fundamental similarities to production order execution. They are incorporating capabilities to build MRO into the Opcenter product as well. They are working with existing customers to capture the nuance required to provide an MRO solution for A&D, for example, planning is very different from using a Bill of Process (BOP) for production vs an MRO service plan, which involves not only quasi-production work, such as upgrading field-based equipment to the latest engineering changes, and scheduled maintenance, but also requires support for unplanned repairs.
The long-term key to SLM success is maintaining an unbroken digital thread between as-designed, as-planned, as-produced, and as-maintained for all product parts and assemblies. This is a tall order, though Siemens claims to be the only vendor that meets DoD needs for MBE to cover things like the overall flow from product design to execution regarding PMI and characteristics, as well as the flow back of that information. It will be interesting to see how meeting these requirements translates into actual success with DoD suppliers that have a lot of compartmentalized thinking and complex supply chains with varying levels of compliance and sophistication.
AI is the topic du jour across all of technology, and Siemens Digital Industries Software is no different (as reported by Tech-Clarity in “Siemens Realize LIVE 2025: A Vision for AI, Simulation, and Immersive Engineering in a Connected Digital Thread”). Siemens Opcenter is also adopting these capabilities. This involves Opcenter integration with Insights Hub (formerly Mindsphere). Insights Hub is dedicated to solving specific use cases and integrates with Opcenter to contextualize Opcenter data. Siemens, along with SIs and customers, uses Insights Hub with capabilities such as Copilot Studio to build their own queries and agentic AI.
In addition, they are collaborating with AI startups – Retrocausal, Cybord, Instrumental – on image recognition, defect detection, etc. They are also creating AI-infused applications with Mendix and its connectors. The UIs are based on Mendix so that they can embed AWS Bedrock, for example. A recipe copilot was created to compile documents, specifications, and other required artifacts from formulated designs for pharma and process industries in one recent case. Early customers have reported up to 3 months of productivity gain to get a drug to market.
Thank you Tobias Lange, Ignace Braem, and Shaun Ennis for this detailed and interesting briefing.
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Can a discrete manufacturer get data from each tool, line, or piece of equipment into an MES and start using it in hours rather than weeks or months? PICO MES was founded to do that, and its Pico MES/IIoT software is now connected and in use at large, medium, and small manufacturers in automotive, aerospace, and other discrete industries.
Pico MES is unusual in the range of sizes of companies using it. Large OEMs with 100s of employees each shift use it, and very small companies with only a few dozen total employees are already using it, too. In 100-200-person automotive and aerospace suppliers, Pico MES can be the full plant floor technology stack. How Pico MES can scale from very small to huge stems from the architecture and the founders’ deep experience.
Telling a worker or machine what to do is central. Pico MES does this by authoring standard work, work instructions, and sequences. Process engineers do this easily using modern drag-and-drop workflows designed. The workflow builder is designed to handle both very simple and highly complex processes, such as nested assemblies. All data feeds into a unified model for context.
The resulting user interface works for both experienced and new workers. Using an opt-in strategy, the basics for anyone appear, and those needing more information can link to additional information or context, whether images or text.
Another element that helps Pico MES serve smaller companies is the speed and ease of connecting to equipment. Since many customers are high-volume, connecting to automation and equipment is crucial. Pico MES claims to have the most extensive library of no-code connections to assembly tools and machines on the market, with over 200 families pre-built. It is essentially a combination of MES with an IIoT platform.
Automation connections are quick and easy to set up. For example, to set up a torque tool, the manufacturer tells the software its IP address, name, header, configuration, how many of them they have, which one to use, where it is located, and whether it’s stationary or used at more than one station. Users can also add safety issues.
The system knows how to collect information and store it without coding. If it’s a new tool that’s never been used, it might take a while to get it connected to the network, but Pico MES says their side only takes five minutes. Based on what we saw, that seems feasible. They know how tools work and that logic works in the background without setup.
Pico MES also connects at the enterprise level to ERP and PLM, which is crucial as a best-of-breed software provider. With all its connectors and no-code workflows, this system can be the single information source for plant floor workers.
Part of the trick for achieving such rapid setup is that Pico MES is a hybrid deployment with a 3-edge architecture (station, factory, and cloud). This architecture with Pico MES running at the factory edge enhances security and resilience in the case of disconnection. The company also offers edge hardware. One edge Pico MES server per factory, plus as many Pico MES Hubs as needed, and the software can run effectively.
Pico MES automatically organizes and displays plant floor data in context. This is a foundation service of MES, but it often takes a long time to structure. In contrast, Pico MES’s unified data model does not need to be customized. Every system can grab all the data it needs from the model, which the founders’ expertise in both factory operations and software enabled them to build from the beginning.
Because of the fast setup, Pico MES offers instant improvement. Beyond the Hawthorne effect, when operators improve knowing they are observed, there’s also error-proofing. This is how they claim 10%-15% output improvements within the first 30 days of use. It also has built-in cycle time analytics to help understand where to focus on less stable processes.
Using Pico MES reduces training time and the potential for errors, which is common for MES. What is not so common is the statistic they cite that output increases 10-15% in the first 30 days. That rapid time to value is rare in the MES world!
Pico MES is already a highly differentiated solution, but there’s more: it can also combine data sets in the cloud and provide supplier visibility for OEMs. Both buyers and suppliers benefit. The instantly available plant data enables a stronger set of data to move between suppliers and buyers instantly if they want.
Tracking and tracing can support higher quality, faster issue resolution, and more precise planning for all parties. Supplier-to-buyer visibility can help coordinate audits, planning, and logistics, track quality and scrap, and match parts to appropriate product uses based on their tolerances. Since 60% of a vehicle's cost comes from supplied parts, the savings can be significant.
OEMs get more value the more of their suppliers make data visible in the cloud through the Pico MES. A Tier 1 supplier can often implement Pico MES for $25,000. Larger implementations have lower per-station setup costs.
Pico MES is venture-backed, and the supply chain opportunity has helped fuel that. Their investors include Momenta (which Rockwell Automation has invested in), Congruent, and industrials such as Schneider Electric and Bosch. Having these outside funds has helped Pico MES expand rapidly to meet customer needs.
We suspect another factor in their growth has been the founders’ coming from running lean operations, not just software companies. They have a fundamental belief that plant people are smart and know what they need to do; they only need tools designed for them to do it. With their background, they understand how to make the software intuitive and low-friction for engineers, supervisors, and operators.
Pico MES’s instant data model will also help gain value quickly from GenAI. Pico MES can train the model on its own real-world data and deploy it to customer factories with no risk of security breaches. It is partnering with Google Gemini to develop a market-ready approach.
Thank you, Ryan Kuhlenbeck and Joyce Yeung, for briefing Julie Fraser on Pico MES. We agree that people in the plants are smart and need simpler tools. Your vision for MES, IIoT, and supply chain capabilities is exciting. We look forward to hearing more of your customers’ successes and value as you expand in the market.
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What will help MedTech companies stay competitive in an era marked by rapid innovation, rising regulatory complexity, and global disruption?
As the industry moves toward smarter, more personalized, and increasingly connected healthcare, MedTech manufacturers face mounting pressure to reduce time to market, improve patient outcomes, control costs, and ensure compliance without sacrificing quality or patient safety. Achieving success in this environment requires digital transformation. With it, MedTech companies can realize greater efficiencies while developing, building, and servicing products and devices across their lifecycle. What should companies consider to successfully select the right solution?
This buyer's guide outlines key buying criteria across four critical areas: software functionality, implementation support, vendor capabilities, and company-specific needs. Based on expert interviews and market research, it's designed to help MedTech leaders evaluate and invest in the tools that will drive innovation, efficiency, and compliance in the years ahead.
Please enjoy the summary* below. For the full research, please visit our sponsor, PTC (registration required).
Operational Resilience
As regulations tighten and risks rise, full traceability has become critical. MedTech companies must demonstrate how decisions are made, how changes affect safety and performance, and maintain compliance from design to post-market support. Legacy systems cannot maintain this end-to-end visibility. A digital thread, enabled by an integrated solution, supports traceability, audit readiness, and proactive quality management.
Overcome Silos
A digital thread links requirements, design, engineering, manufacturing, quality, and service, making every decision traceable, every change visible, and every team aligned. Traceability accelerates root cause analysis, simplifies compliance, and improves first-time-right development. When requirements are linked to test results, quality and regulatory assurance become built-in.
By integrating Application Lifecycle Management (ALM), Product Lifecycle Management (PLM), Quality Management Systems (QMS), ERP, Manufacturing Execution Systems (MES), and Service Lifecycle Management (SLM), companies improve collaboration, manage requirements, plan for manufacturing, and leverage real-world service data in a shared digital environment. This integration yields numerous business benefits (see graphic).10
Prepare for the Future
This approach enables MedTech companies to transition from document-based processes to data-driven development, integrated quality systems, and connected service operations. It provides the agility needed to thrive in today's disruptive environment. The right solution will also support next-generation capabilities like AI, digital twins, and open interoperability.
Recently, we attended Realize LIVE 2025 events in both Detroit and Amsterdam. During these events, Siemens presented a clear and cohesive vision for helping customers manage increasing product complexity through digital transformation. This vision incorporates AI, cloud technology, a comprehensive digital twin, and an industry-tailored digital threads.
Across multiple presentations, starting with the vision shared by Siemens Digital Industries Software CEO Tony Hemmelgarn, Siemens positioned itself as a company dedicated to solving practical engineering challenges while embedding intelligence directly into workflows, integrating advanced simulation and AI, and closing the loop between design, manufacturing, and operations.
It was a wide-ranging program, but several consistent themes demonstrated how Siemens plans to realize this vision. While we can't cover everything discussed during the multi-day event, here are some highlights that stood out to us.
While new technologies like AI and immersive engineering draw attention, Tony Hemmelgarn reminded attendees that some of the most critical engineering challenges are deceptively "unsexy." He highlighted BOM management as an example. "It's not the most glamorous part of what we do," he said, "but if you can't manage your BOMs effectively, you can't make the right product, at the right time, at the right cost."
BOM management has become increasingly complex due to product variation, shorter cycles, and cross-domain dependencies. By embedding BOMs into the digital thread and connecting them to design, simulation, and manufacturing execution, service, and even supply chain, Siemens aims to prevent data mismatches and costly downstream errors. They highlighted several Teamcenter enhancements they’ve worked on:
This focus on fundamental engineering execution indicates Siemens' commitment to solving core problems while also delivering next-generation technology.
Siemens positioned AI as an embedded capability that "works in the background," enhancing productivity without requiring process changes. Instead of being offered as a separate product line, AI is integrated throughout the Siemens Xcelerator portfolio, manifesting in generative design, automated simulation setup, manufacturability checks, and lifecycle intelligence, among many other areas.
We have been monitoring AI adoption, usage, and benefits through multiple studies. In our annual survey, Executive Strategies for Sustainable Business Success 2025, we found that since 2024, the percentage of companies reporting business value from AI has increased by an impressive 62%. In fact, AI was the technology most frequently cited as providing substantial value. Another research study, Making Manufacturing Analytics and AI Matter, indicated that AI is the technology most likely to yield a rapid time to benefit compared to others.
Tony shared an example of AI-enabled BOM management, "We asked Teamcenter to analyze warranty hotspots. AI interpreted severity and growth potential, pinpointed a problematic connector, created a change request, assessed supply chain risks, and found the best replacement, all automatically documented and visible to stakeholders."
This flow, from detection to resolution, demonstrates how Siemens is incorporating AI to accelerate decision-making, break down silos, and turn data into actionable insight. Joe Bohman further illustrated these capabilities by describing AI-assisted design optimization that happens in real time and design validation that flags production risks.
Tech-Clarity's research, The Business Value of Reducing Engineering Time Wasters, found that 96% of surveyed companies acknowledge that lost engineering productivity leads to significant business costs due to missed deadlines, higher expenses, decreased innovation, and poor quality. AI-embedded workflows like this show substantial potential for overcoming these challenges.
Speakers repeatedly emphasized that simulation is central to Siemens’ comprehensive digital twin strategy, enabling companies to validate, optimize, and certify designs virtually, before committing to the physical product or prototype. The Simcenter portfolio supports multi-physics, system-level, high-fidelity simulation, with applications spanning multiple industries such as:
The recent Altair acquisition adds electromagnetic modeling and AI-driven process optimization, complementing Simcenter's existing capabilities. Altair SimSolid is a particularly exciting addition, as it eliminates the time-consuming geometry preparation and meshing process for analysis, providing design engineers with easier access to simulation for design guidance. During the Media and Analyst session, they also demonstrated simulation capabilities beyond Simcenter in EDA to support semiconductor lifecycle management and board design optimization.
At the core of Siemens' vision is the digital thread, an execution framework that links design, sourcing, simulation, manufacturing, supply chain, and service data in a cohesive flow. This framework also serves as the foundation for Siemens' comprehensive digital twin, which not only represents the product, but also encompasses production processes and operational behavior over time.
Siemens presented digital thread use cases spanning multiple industries, for example:
The key takeaway is that data should not merely be stored; it must be connected, contextualized, and utilized to inform better decisions throughout the product lifecycle.
During the NX keynote, Robert Haubrock introduced Immersive Engineering featuring a purpose-built Sony headset with "4K resolution per eye," which is available now. This resolution exceeds what the human eye typically perceives. Siemens views this technology as a tool for more intuitive design reviews, allowing engineers to walk through models, identify spatial issues, and collaborate in real-time. Bob emphasized, "The only way to understand it is to put it on your head." Beyond enhancing productivity, Siemens positions these immersive tools as appealing to the next generation of engineers, accustomed to interactive, high-fidelity experiences from the world of gaming. Our surveys and discussions with manufacturers show that AR/VR adoption is still low, but we believe it can provide significant value, especially as innovations around complementary technologies grow.
Siemens highlighted the scalability of its design platform, Designcenter, which encompasses both NX and Solid Edge. For more on Designcenter, see our previous commentary in A Siemens NX Update: Extending Access and MBE. With this platform, the company is committed to making advanced capabilities more accessible by offering value-based licensing models. This approach allows customers to access features without investing in full enterprise suites.
Further, Siemens continues solidifying its position as a foundational technology provider, claiming that over 70% of the global solid modeling market relies on its PLM Components technology, including its kernel, Parasolid, also common across both Solid Edge and NX. This strategy promotes openness with third-party applications, facilitating seamless data flow between systems that use the same kernel. Additionally, this foundation supports AI-based applications that can leverage data across various platforms and tools.
Siemens continues to expand access to digital capabilities through Mendix, its low-code application development environment. Mendix enables non-IT specialists to create applications, adapt core applications, automate workflows, and integrate data. By doing so, low-code technology broadens the reach of the digital thread across the enterprise, accelerates transformation, and allows more stakeholders to participate in problem-solving. Mendix extends Siemens Xcelerator capabilities and promotes further adoption by allowing companies to develop purpose-built, composable applications to meet the unique needs of their people. For more of our analysis on Mendix please see Adapt and Extend Applications with Mendix.
Siemens' cloud vision centers on delivering its Siemens Xcelerator portfolio as SaaS, with offerings such as NX X, Teamcenter X, and other "X" solutions. Their approach focuses on flexibility, scalability, and continuous updates, eliminating the IT overhead associated with traditional deployments. By hosting design, engineering, and manufacturing solutions in a secure, integrated cloud environment, Siemens aims to enhance collaboration, simplify adoption, and make emerging technologies like AI more readily available to customers. Tech-Clarity's research, The Business Value of Reducing Engineering Time Wasters, respondents reported that cloud-based solutions were implemented in nearly 50% less time than non-cloud alternatives. Further, 78% of those who described their implementation as "easy" had deployed a cloud-based solution.
In summary, here are some key strategic implications from the vision presented at the events:
One of the notable aspects of Siemens' presentations was the balance between forward-looking innovation and the practical realities of day-to-day engineering. Exciting concepts like high-fidelity simulation, AI-assisted design, and immersive virtual reality (VR) were complemented by a strong emphasis on BOM management and the execution framework of the digital thread. This demonstrates Siemens' understanding that attention to fundamental aspects is just as important as pursuing breakthroughs.
We look forward to seeing how Siemens evolves its vision into mainstream engineering practices, especially with the exciting developments in physics AI that promise to make simulation tools even more accessible.
Tech-Clarity's research, How to Engineer Innovation, found that an overwhelming 99% of respondents find benefits in using simulation to explore design ideas to innovate and optimize designs in less time. Still, most agree that they could leverage simulation more effectively than they currently do. Integrating AI could be a key factor in unlocking even greater value from simulation.
Thank you to Shaun Ennis, Heike Hofmann, and Julia Martin for the invitation and all the coordination to ensure we made the most of our time at the event. We'd also like to extend a special thanks to Brenda Discher, George Rendell, Tom Spangler, S. Ravi Shankar, Jean Claude Ercolanelli, and Jennifer Ferello for their thoughtful discussions and meeting with us one-on-one to answer our questions.
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How can machine builders improve engineering productivity?
Industrial machinery has become increasingly complex, with even more mechanical components, electronics, and software. Customer needs for improved maintainability, increased automation, and better efficiency have driven this complexity further. Engineers are critical to successfully meet these requirements. Yet, engineers regularly lose productivity to non-value-add tasks that not only rob them of their ability to innovate, but also threaten their company’s ability to compete, differentiate, and grow. Imagine the potential of identifying and removing the most common non-value-add activities engineers face and empowering them to focus on designing better machines.
This research examines how engineers spend their time, where they lose productivity, and the impact on the business. It then identifies solutions and approaches to reduce time wasters. Based on a survey of 228 manufacturers across industries, this report shares the results of the industrial equipment industry and looks at their challenges and opportunities from the perspective of industrial machinery companies.
Please enjoy the summary* below. For the full research, please visit our sponsor, Siemens (registration required).
This report is based off the research published in The Business Value of Reducing Engineering Time Wasters which takes a look across all industries.
For other industry-specific related research, read:
Product Development Is Critical to Business Strategies
Machine designers also waste efforts redoing work. They waste time recreating what they can’t find or fixing errors due to outdated or conflicting information. Better methods to centralize access to data would help get that time back.
Given how fast technology and markets are changing, how can manufacturers of intelligent products ensure they are ready for what’s next? Future-ready manufacturing requires plant floor systems that go beyond traditional manufacturing execution systems (MES). With the full scope of manufacturing operations management (MOM), analytics, and artificial intelligence (AI), companies have a good opportunity to be agile enough to make the next pivot. This eBook explores all of that and more.
Please enjoy the summary* below. For the full research, please visit our sponsor iTAC Software (registration required).
Modern software should include an engine for machine learning and artificial intelligence (ML/AI). Look for models trained based on the MES provider’s expertise. The AI capability must span specific production environments that the engineers know, not just data scientists. The beauty of ML, as the name suggests, is that it learns from reality. In this case, the MES data reflects reality and teaches the model. Sometimes, the MOM offering also includes a toolbox of algorithms that can deliver automated insights.
At the Speed of Operations
What’s crucial is that the analytics, AI, or ML provide results fast enough for the operation to use them effectively. Event streaming can add speed and agility. For maximum effectiveness, the system will also deliver alarms and escalation when anomalies occur. Decision-makers often need to know right away.
Optimizing Analytics
While basic analytics are standard for MES, some special factors can optimize analytics. These include:
We recently had the opportunity to speak with Denis Morais and Greg Goulanian from SSI. SSI offers specialized solutions for the design, engineering, construction, and maintenance of shipbuilding projects. We’ve known SSI for years and realized that their strategy had shifted so felt it was time for an update.
SSI focuses exclusively on the shipbuilding industry, with over 30 years of experience that has given them deep expertise in this highly specialized domain. Their two flagship offerings are:
Purpose-Built for Shipbuilding
SSI’s technology is designed specifically around how ships are engineered and built. Their data models, workflows, and terminology reflect the language and logic of shipbuilding, with native support for concepts like hulls, outfitting, and vessel configurations. Even within the same class of ship, design and manufacturing vary based on the shipyard, and SSI accounts for that. Their platform supports the design, construction, and maintenance of multiple hulls in a series, production planning, change and configuration management, and digital ship handover.
Fast Implementation / Time-to-Value
SSI says that their standardized implementation approach enables them to bring full shipbuilding PLM environments online in as little as 1.5 to 2 months. They say most projects go live within 2 to 6 months, even in complex defense environments. Their ability to import data and documents from legacy systems helps even smaller or repair-focused yards move quickly.
Expertise-Led Configuration
Every SSI implementation is led by people who know shipbuilding inside and out. This deep domain knowledge allows their team to deliver faster, more relevant, and lower-effort deployments for shipbuilding. All clients start with the same foundational data model, with customization happening at the workflow level, such as change approvals or configuration management. The result is a solution that fits naturally with how shipyards operate, without relying on heavy custom coding or large consultant teams.
Strong Technical Foundation
SSI’s PLM platform is powered by Aras, but extensively tailored to shipbuilding. They’ve built in custom data models that span requirements, work breakdown structures (WBS), MBSE, and shipbuilding-specific change and configuration management workflows, which they report enables a unified model that supports full traceability and engineering, planning, and production team collaboration. They’ve extended the platform to manage functional design, ship-specific WBS models, and Navy-specific requirements around approvals and lifecycle documentation.
Open Architecture
SSI has a fully open data model with complete API access. This openness allows shipbuilders to integrate SSI’s tools with external solutions, ERP, MRP, MES, CFD software, training tools, or visualization platforms like Canvas GFX.
SSI helps their customers solve a wide variety of challenges:
Planning and Scheduling
SSI helps coordinate across the many partners involved in a ship build. From design agencies, contractors, or the shipyard itself, their shared platform facilitates schedule alignment and better decision-making, especially projects with complex workflows such as Navy-focused projects.
Early BOM Access and Long-Lead Purchasing
Shipyards often need to make early material purchases, like steel or piping, well before the full design is finalized. SSI enables the creation of preliminary BOMs to support those decisions, helping procurement teams act with more confidence and reducing the risks that come with long-lead items in evolving designs.
Cross-Partner Collaboration
SSI provides a common platform that enables real-time collaboration between all players in the shipbuilding ecosystem. Engineers, subcontractors, and manufacturers all work from the same source of truth, providing needed transparency as the design evolves.
Change Management and Compliance
SSI’s platform supports the specific requirements of defense programs, including Navy-specific approval workflows (such as for penetrations, the openings or holes cut into structural elements, such as bulkheads, decks, or hull sections) with full lifecycle traceability to support a digital thread. This traceability supports change management and compliance processes across one or multiple hulls.
Clash Detection and Model Integration
SSI enables simultaneous modeling of structure and outfitting, allowing yards to run clash detection early to catch potential problems in a digital environment, helping to avoid rework later on.
Tech-Clarity’s research, published in Reducing Engineering Time Wasters in Shipbuilding, finds that 87% of companies developing complex products, such as ships, say lost engineering productivity comes at a significant business cost due to missed deadlines (reported by 63%), inability to stay on budget (44%), less innovation (38%), higher costs (38%), and poor quality (25%). In fact, 59% report that time wasted on non-value-added work is the top thing that slows engineers down.
Our research has found that those who have adopted PLM/PDM find it helps reduce much of this non-value-added work. Those working on complex products like ships report that PLM helps them in these ways:
We believe there’s a lot of opportunity for improvement in shipbuilding and these results show how a PLM solution could enable those improvements.
For an industry like shipbuilding, the specialized needs and high levels of complexity mean implementation industry expertise is essential. SSI’s ability to deliver fast, under-budget projects without heavy onsite support is a testament to how well their platform fits the unique needs of modern shipyards. We’re also watching with interest as SSI moves beyond engineering to support broader yard-wide objectives, and as they expand internationally.
Thanks again to Denis Morais and Greg Goulanian for the informative conversation.
[post_title] => SSI: Shipbuilding Platform That’s Purpose-Built from the Hull Up [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => shipbuilding-ssi [to_ping] => [pinged] => [post_modified] => 2025-10-01 23:27:43 [post_modified_gmt] => 2025-10-02 03:27:43 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=22928 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [18] => WP_Post Object ( [ID] => 22756 [post_author] => 2572 [post_date] => 2025-09-10 07:00:57 [post_date_gmt] => 2025-09-10 11:00:57 [post_content] => What are your biggest electrical design challenges?
We are researching electrical design, including top challenges, identifying the most time consuming tasks, the impact of greater automation, and how poor collaboration between electrical and mechanical engineers affects the development process. We will also use the results to identify best practices. The survey takes about 10 to 15 minutes.
If you are familiar with the electrical design work at your company, either by doing the design work yourself, collaborating with those who do, or managing electrical design teams, please take the survey to share your thoughts. As a thank you, we will send you a copy of the report summarizing the findings.
In addition, respondents will be entered into a drawing for one of 20 $25 Amazon gift cards.*
Individual responses will be kept confidential. Please feel free to forward this survey to others you feel have an opinion to share.
Thank you for your support, please check out our Active Research page for additional Tech-Clarity survey opportunities.
*See survey for eligibility rules
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We’ve been researching make-to-order (MTO) and engineer-to-order (ETO) approaches for over two decades and we’ve witnessed continued growth in product customization. We’ve also watched configuration approaches and technologies evolve. Two things have been consistent over time:
What else has changed? We recently surveyed over 200 companies that manufacture to-order products to find out.
I recently had the opportunity to sit down with Rick Smith , Director of Engineer to Order Solutions at Siemens Digital Industries Software, to get his perspective on our survey and configuration and MTO (make-to-order) trends. I’ve worked with Rick on some of our research, including his participation as a contributing subject matter expert for our recent Making To-Order Product Configuration Profitable survey. I’m always excited to learn from his experience working with customers in the MTO and ETO (engineer-to-order) space.
Jim Brown
Hi Rick. Will you please introduce yourself and your company, and let us know your role with configurators and to-order products?
Rick Smith
I'm Rick Smith with Siemens Digital Industry Software. I'm a product manager for the Rulestream product line. Siemens has a very broad portfolio of engineering and manufacturing software, of which Rulestream is the solution for engineering automation. It works very closely with Teamcenter, our industry-leading PLM system. Rulestream interfaces directly through Teamcenter to a large number of the other solutions in the Siemens software portfolio, so it’s integrated to a complete set of design and CAE (Computer Aided Engineering, or simulation) tools.
Jim Brown
Rick, I always appreciate your enthusiasm as much as your expertise. What gets you jazzed about to-order manufacturing and configurators?
Rick Smith
The excitement goes back to the early 2000s when I discovered the profound impact an automation solution could have on the world of manufacturing complex products. I always suffered from the inefficiencies of the available tools and thought there had to be a better way to do it. In my early exposure to Rulestream (as a customer), I realized that it is a really different way of doing things, giving me the tools that I need to be more productive not only as an engineer but also across the whole business in terms of accuracy and efficiency.
Jim Brown
Thanks Rick. I’m excited to talk about the research with you. The survey looked into why companies configure products. The results show a variety of reasons. The top two, differentiation and higher prices, are about the ability to attract business and profit from it. For them, it’s about revenue and profitability. But sometimes companies don’t have a choice. In fact, our studies often show that providing to-order products is a “must have” for their industry.
Rick, you’ve been working in the space for a long time. Why is making products to order so compelling?
Rick Smith
I think there are several reasons, and it depends on the company and the industry. For one industry, it may just be the nature of the beast. If you're building a solar or a wind solution, you want to use every square inch or cubic inch of space to generate as much income as possible. That means that you want to put up as many solar panels or as many turbines of the right size to fit the space available. Or, if it's a hydro dam, you want to get more kilowatt hours or KVA from the same amount of water. Can we get a more efficient turbine? Can we get more efficient distribution? All of those things require engineering to customize the solution to the unique requirements of the request. By choosing to be in this industry, you chose MTO.
Jim Brown
The next most common response is to sell standard products. In this case, selling customized products is a necessity for commercial rather than technical reasons. What creates this scenario?
Rick Smith
One way this happens is in industries that are commoditized or commoditizing. If customers are consolidating their spend and a manufacturer can offer customized products alongside their standard ones, they choose the company that can offer related products that are configurable, allowing that company to sell more standard products and become the supplier of choice.Making To-Order Product Configuration Profitable, Tech-ClarityMaking To-Order Product Configuration Profitable, Tech-Clarity
Or, they're in a commodity business and they recognized that if they can offer a customized solution at the same cost and lead time as their competitors are offering standard solutions they can take over the market. We had just one such company do that with a commercial air handler, a very competitive business, and they became the number one supplier of that product in the world.
Jim Brown
Configured products are compelling and companies don’t seem to be able to get enough of them. Our research from five years ago showed that the majority of companies were increasing the amount of configuration in their products, and it jumped again during our latest study with 94% saying it will grow over the next five years.
Why do you think customization continues to grow?
Rick Smith
It's all the reasons that we just talked about that drive the desire to do it. Everybody wants a product that is tailored to their unique needs, right? But
I think more companies are moving towards it because their competitors are and they want to either lead or catch up. Just the HVAC example that we talked about, right? They killed their competitors because they offered a custom product.
I also think it’s because automation makes it more cost-effective. Engineering software can do more for to-order manufacturers than ever. It now takes them less effort to support customization across their business because the technology can accomplish more for them and is more integrated into other engineering and manufacturing applications.
Jim Brown
One of the things we looked at in the survey was best practices to increase profits from to-order products across different aspects of their business, including engineering. I know you and I are both engineers, and we found best practices there, but let’s focus on sales. We analyzed what top performing companies do differently in the selling process.
One of the things that we saw was moving configuration closer to the customer, or “shifting left. About one-half of all respondents have taken steps to shift configuration left, such as from sales engineers to salespeople or from distributors to customer self-service. Almost all, a full 90% of responding companies, have, or would like to, shift configuration closer to the customer. Why do you think that the manufacturers are moving detailed configure order entry towards the customer?
Rick Smith
Making To-Order Configuration Profitabile, Tech-ClarityPart of it I believe is due to demographics of the people who are buying. I was a chalkboard and slate guy. There are people today that were born with technology in their hands that expect the ability to chat to their friends at any point in time. So their expectation is I want to do whatever I want to do when I want to do it. They want self-service.
I think part of it is to be easier to buy from. So, we always talk about the sales process. I want to talk about the buying process, which is the more important part. Customers are going to buy from whoever they can buy from the easiest, so long as it is a good solution at a competitive price. It doesn't even have to be the lowest price necessarily, but they're the easiest to buy from. The same is even more true for distributors that may carry different product lines. They don’t necessarily care which line they sell, so they are motivated to sell the one that is easiest to order.
Another proof point that the shift left is happening because is that the survey says companies need mobile device support. Ten years ago, you were not going to buy anything on your phone. Now, it's required because people expect to be able to configure and order things from their mobile device.
Jim Brown
Great insights. Well, we know it’s valuable because Top Performers are 74% more likely to have significantly shifted configuration left than poorer performing companies. As I mentioned, we also identified best practices for engineering techniques, but we’ll have to save that for another interview.
Jim Brown
There are a variety of technologies available to help companies reduce (or perhaps embrace) the complexity of configuration. Sales configurators, engineering configurators, and simpler CPQ solutions. Top Performers are more likely to use configurators in general. But what really stood out is that they’re also more likely to use advanced configuration functions like of drawing creation, CAE automation, 3D visualization, and engineering calculations.
Rick, this reminds me of the automation you spoke about earlier. In the survey report, we interviewed a customer who says they reduced engineering hours from CAD automation that works hand-in-hand with their PLM. The Top Performers also say it helps them grow revenue and profitability.
Why do you think these capabilities are correlated with improving operational and business performance of their to-order products?
Rick Smith
I think there's two things. It allows them to create a better quality design and a better quality bid package. That’s a start. But the types of products that our customers sell are not simple products, right? There are calculations that need to take place. There are a lot of very good CPQ systems with good configurators built into them, but those are not really built for technically complex products. The industries targeted in the survey included heavy equipment, industrial machinery, agriculture, and energy equipment. Those products require more industrial strength, if you will, configuration technologies.
They need better tools to get the value they want. For example, the survey showed the leaders use substantially fewer engineers in the bid process. It's because those companies use the more sophisticated tools that are capable of doing more of what an engineer does as part of the sales process. The market leaders have figured out how to get the engineers to invest their brains into the configurator so they can go off and build new, exciting things and they don't need to be a part of creating the bid package.
Jim Brown
So not only are the Top Performers able to create better-configured order designs and design deliverables, but they are also doing it more efficiently, responding more quickly and freeing up engineering resources at the same time?
Rick Smith
Exactly!
Jim Brown
Let’s drill down on technology. Our research shows that companies are getting significant value from AI, and we’ve even seen that AI is providing benefits faster than other technologies. We haven’t studied the use of AI for configuration, although it seems like there could be significant value. I have to imagine you have looked into the value of AI for product configuration. Is there real value, or are we just in a period of hype?
Rick Smith
There is a ton of excitement. I think you’re right that it is a little bit early, and I think some of it is misunderstood. One of the areas where we can see direct applicability of AI is getting specifications right. A customer may provide a spec document and drawings. Then, a sales engineer opens it up with a yellow highlighter (or virtual yellow highlighter) and reads through those requirements and the drawings and creates takeoffs. That’s a perfect application for AI, and there are solutions available to help with that today. That directly replaces manual effort.
Another area that's very interesting is being able to get more information out of your configuration knowledge. Configuration rules have typically been expressed in a form that a solver can use, whether it's declarative, closed form, constraints, or whatever. You could use AI to interpret it and give you back that knowledge in a format that people can understand, validate, and reuse.
Jim Brown
That’s very interesting. Will AI replace traditional configuration techniques?
Rick Smith
I don't think they're going to replace the automation or configuration solutions. And here's why. You need to train AI. But how many designs do most companies have that actually follow their design best practices? The designs may include changes to address a supply chain event or may be prior to a cost engineering event. Do they have enough designs to cover the full range of product variability in the way they design today? Automating outdated rules does you no good. And even if AI got you 80% of the way there, well-formed automation or well-formed configurators give you the right answer 100% of the time.
In the next several years, I do think AI can be used to help feed configurators the rules. That’s something that's done by hand today and can be assisted by a co-pilot.
Jim Brown
The last question I would ask you is if you were working for a manufacturer and trying to figure out what you were going to do around configuration, what advice would you give yourself?
Rick Smith
I did not have an answer thought through on this one. I think there are three things I would say:
First is to understand your product space, your competitive landscape, your market, and the trends for the future. Don't just try to solve today's problem.
The second thing is be careful. You need to leverage the experts and ask them counter questions. We’ve seen examples where consultants have recommended an approach like shifting from ETO to MTO that was fundamentally unachievable. That company wasted a lot of time and money, and ended up losing significant market share. Work with people who understand configuration.
Finally, look at a platform. You want to have a platform that's going to be around because you're going to be investing in it. Look at companies that have proven track records, are continuing to invest in their solutions, and are investing in the integration of solutions. Point automation can be helpful, but optimizing for an entire business process is even more powerful. Configuration is not trying to automate one little thing, it's trying to optimize an overall digital thread, a business process for to-order products.
Jim Brown
That makes sense. Configuration doesn’t only touch Engineering, it impacts across the enterprise and the supply chain.
Thank you Rick. That’s all we have time for. As we concluded in the report, we believe that the use of product configurators is a basic necessity for designing, selling, and delivering to-order products, but that companies who adopt proven best practice engineering, order, quote, and technical enabler gain significant advantages that translate directly to improved revenue and profitability.
There is more information available in the underlying survey report, including interviews with Schumacher Elevator Company and Ingersoll Rand. You can view a summary of the research on our site or download the full survey report courtesy of Siemens.
Thank you for the conversation Rick, I always learn something new when we talk!
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