Addressing Pain Points
Addressing Pain PointsHow can innovative high tech companies keep working with the same MES provider for decades? Some work with camLine, an Elisa IndustrIQ company that has been building software to solve specific customers’ operational problems for over 30 years. It appears camLine and its customers are constantly creating fresh and powerful modules together.
Many companies start by solving specific customer issues and then turn that into commercial software. For camLine, that is a formula for ongoing innovation and market success. They are proud that their software development begins with real customer issues, not in an R&D lab.
End-to-End Suite
As a result of decades of this collaborative problem-solving becoming commercial software, camLine has a broad set of modules. MES is at the center, complete with equipment integration, enterprise integration, visualization, and scheduling. camLine also offers supply chain tracking and supplier quality management, customer quality management, container distribution management, and material control. The camLine product suite also includes Cornerstone for engineering data analysis with design of experiments (DoE) and XperiDesk for process development and tech transfer to scale up. Traceability and enterprise quality data lakes support these applications.
This suite goes from suppliers through shipping and product and process design into successful operations sustainment. We see that MES is at the center of the supply chain and the product lifecycle. camLine has addressed much of that by extending beyond traditional MES boundaries into areas that touch it and impact customers’ operational excellence.
Incremental Implementation
Despite the extensive scope of its software, camLine is dedicated to enabling customers to get what they need when they need it. The modular approach allows customers to activate different modules and replace their existing systems step-by-step, lowering their risk compared to replacing an entire live MES.
While they educate customers about the full capabilities of the entire suite, they support this piece-by-piece change. As with their approach to software development, it all starts with understanding the customer’s pain points and addressing those. So quality, scheduling, security, AI, DoE, logistics, monitoring, or process integrity modules can go live independently of other modules.
Innovation Industries
We were surprised that in addition to electronics, semiconductor, solar, automotive, lighting, and medical device segments, camLine has also long served advanced materials. The common thread is a focus on constant and short-cycle innovation, where production process engineering is critical to product quality and consistency. camLine’s combination of MES with engineering data analysis and process development clearly speaks to this type of company.
The relationships camLine forms with its customers are remarkable. As a result of their relentless focus on solving outstanding problems, they collaborate closely with early adopters. Translating that into software that customers at any stage of maturity can use over decades also cements a deep, long-term understanding of long-term customers’ operations and needs.
Engineering Better Outcomes
From camLine’s perspective, artificial intelligence (AI) is not the panacea but rather a tool to use when process design fails. It leverages its (often vast) process database and analytics-focused data lake to see what went wrong when the process design fails. With their process design expertise, they can see how AI’s findings can feed back into their process development and DoE tools.
Starting at the engineering level is a superior approach in our view to simply detecting anomalies. A new process design can eliminate the root causes of issues and thus can improve performance on an ongoing basis. Engineers know that but don’t always get the benefit of collaborating with the operations team to achieve it based on trusted shared data. The automation layer ensures direct equipment data goes into all applications and is ready for analysis and AI.
Another aspect of engineering is supplier quality management. This is not a new area for camLine but one that more customers are adopting. End-to-end traceability with RCA can foster stronger customer-supplier relationships and faster decision-making. The system is designed to accommodate suppliers with a less mature digital infrastructure through email communication on predefined parameters.
AI for Customers
Helping people detect and predict anomalies with possible root cause analysis (RCA) presents a robust set of use cases for AI. It requires computing power and access to the entire relevant data set to make good decisions in real time. The benefits of not processing a bad product further or adjusting the following steps to compensate for the in-process product characteristics are enormous. camLine has most of the data on relevant variables in its data lake and can easily add other data sets.
At its recent customer event, camLine Forum, customers shared mainly human-centric automation stories. The real-time aspect of these AI implementations enables corrective action to begin immediately.
- One large semiconductor customer discussed fab efficiency using SPC and multi-variate analysis algorithms to detect good vs. bad wafers. Using 10-20 dimensions in a single KPI, they can replicate and visualize the wafers and use machine learning (ML) to control parameters and reduce false alarms in run-time. This is now available to other customers.
- This same customer has an AI algorithm that indicates the most likely root cause of anomalies. Traditionally, when an exception is detected, they attribute it to the previous step, but this algorithm looks at all previous steps and seeks to identify root causes in real-time. This avoids replicating problems, enables correction or rework before the next process, and improves tool uptime as there is no need to stop the lot and equipment for manual root cause analysis.
- A battery manufacturer accelerated its time to go from lab to manufacturing. This yield-enhancing RCA identified degradation causes and hidden dependencies in a very complex process. In this example, after only 15 cycles, they can now predict with 99.8% accuracy whether a cell will reach over 1000 cycles. This reduced a 42-day cycle in the lab to 14 hours in the plant. They gained more information and saved time, people, and money.
What’s Next
Building out more applications that leverage AI is clearly on the roadmap. Currently, most of the customer AI use is among early adopters. As camLine enriches the portfolio with these, followers and even laggards will also be able to benefit. camLine brings a mindset to AI of not only “what is the insight?” but “what action can we take to protect the material or process and avoid things going wrong?”
These innovation industries, such as semiconductors, photovoltaic, and batteries, are seeking the next technology and materials improvements in their products. The only way for them to get to stability in a new technology is with advanced algorithms to understand the products and processes as they change. camLine has its own AI team, as does parent Elisa. Combined with camLine’s statisticians, industrial engineers, and others who know the processes, this company is well-positioned for growth in AI.
With the broad set of data it collects and analyzes across the many application areas, camLine is aiming to productize an approach to calculate and deliver visibility into a facility’s carbon footprint. Our research shows that manufacturers are getting serious about environmental sustainability, so the timing is good.
More to Come
We have visited with Elisa IndustrIQ and some of the other companies in that group. The proven software groups getting an injection of global team and AI capabilities is impressive. Thank you, Duncan Chapple, for setting up these meetings. Thank you, Danny Kwang, and Stephane Allard, for sharing your time to explain camLine’s culture, approach, and successes with us. We look forward to following camLine’s continued progress in the market.