Preserving critical plant knowledge is essential for the digital transformation journey
Information on plant operations between teams is exchanged during daily activities, much of which can be essential to managing ongoing plant processes. If this tacit knowledge, particularly between operational teams and shifts, is captured in a digital “knowledge bank” with intuitive access, process manufacturers can be more efficient, safer and more competitive. Andreas Eschbach, CEO and founder of eschbach’s Shiftconnector platform, discusses how artificial intelligence (AI) can help support the capture and sharing of this institutional knowledge and why it is important as process manufacturers move to Industry 5.0.
Q: What challenges related to knowledge management do you think process manufacturers will be facing over the next five years?
Over the next few years, about 25% of chemical industry workers will be eligible to retire. For many process manufacturers, this could translate to a significant loss of skill, experience and critical plant knowledge — all of which could negatively impact productivity, safety and overall profitability.
Process manufacturers rely on knowledge management, which is the process of creating and maintaining information related to a manufacturer's operations, shift-to-shift or team communications as well as sharing vital operational process information enterprise-wide. Often, the most difficult knowledge to capture is tacit knowledge where a long-time worker has gained extensive knowledge about plant operations throughout the years.
Q: With this in mind, how do companies capture and preserve critical plant knowledge that exists only in the minds of these workers?
For starters, it is vital to establish knowledge-creation processes and techniques to preserve and build upon institutional knowledge. There is know-how among teams and individuals, which needs to be preserved in a structured way so that it can easily be shared across the enterprise, including multiple and geographically dispersed plants.
Knowledge management is a domain-specific discipline. There is formal (explicit) vs. informal (tacit) knowledge. Digitalization is critical to capture both types of knowledge, so it can be shared across teams, new employees and the entire organization. Tacit knowledge is trickier to capture, so digitalization can help an organization not only capture the information but use it where and when it is needed most.
Q: Can tacit knowledge be combined with any new technologies to help solve this potential loss of skills, which is a major challenge for process manufacturers?
Yes. Tacit knowledge, otherwise known as "people experience" within processing plants, integrated with the power of AI, can drive innovations that will help manufacturing teams solve complex problems and expand ingenuity in the process. For instance, AI-enabled systems can keep track of operational teams’ activities, thus increasing efficiencies and asset performance. An AI system enables the retrieval of collected data enterprise-wide, enabling real-time access to pertinent data to address specific productivity issues when they arise. The use of machine learning, for instance, allows for continuous input by workers to teach a smart search to retrieve more relevant information faster.
Q: Can you give a real-world example?
For example, one area that is noteworthy is the essential knowledge transfer that occurs between shifts. It is important to take a people-centered approach that looks beyond digitalization and considers the needs of people using these tools. What do they need to know and when? What kinds of decisions do they need to make and who else needs to be involved to facilitate critical decisions?
Consider a day-shift technician in a chemical processing plant. At the start of their day, they need to quickly come up to speed with the status of the processes inherited from the night shift and what, if any, next steps are required. They also need to know if there are any problems to troubleshoot, new directives from management or safety or maintenance issues that need attention. While some information can be conveyed during a shift handover meeting, other data tends to be scattered among logs and documents, often maintained in siloed areas of the plants — unshared and not transparent.
In all user cases, visual management is used as an efficient management approach to engage people on the shop floor to improve production capacity. Visual management empowers frontline personnel with data and engages them to make data-driven decisions. It allows for the visualization of batch cycle times, process variations and overall equipment effectiveness (OEE) losses.
Executing continuous improvement initiatives requires a 24/7 commitment by every shift team. To accomplish this, everybody needs to be on the same page to support plant objectives. The key is to make sure improvements are owned by the people involved and supported by digital applications that deliver data from everywhere in the plant and can be accessed whenever and wherever it is needed. For instance, when operations personnel such as engineers are working from home, the KPIs with their targets and actual results must be made available onsite or remotely.
Q: What KPIs should be considered?
Certain KPIs can measure the asset utilization of a single plant and deliver insight into an enterprise’s network of manufacturing plants around the globe.
One of those KPIs is OEE, which considers the effects of the many different work processes influencing output, from demand generation and planning to operations and asset maintenance. OEE strategies have become instrumental in monitoring these processes. For instance, for a single plant or process cell, OEE has been proven to yield improvements in production rates.
What is also important for a plant’s KPI is to always have meaningful figures and data at hand to enable quick decisions on possible optimizations. Data also provides the opportunity for transparent and unified measurement of asset utilization for both manufacturing management and frontline workers.
Q: As process manufacturers continue their digital transformation journey and embrace Industry 5.0, what do you think will be some of the positive outcomes?
Industry 5.0 ushers in the smart factory and people and machines working together. It is the promise of moving beyond focusing on just the machines and empowering people. With the power of AI, people and machines can work together to improve operational performance, quickly solve problems and accelerate the pace of improvement. New systems that are part of a plant process management approach have the power to capture the full organizational knowledge of the workforce across multiple systems and sites and can make that knowledge easily available to all team members in a way that will benefit their contributions to the company.
Like all technologies, AI tools will continue to evolve, creating exciting new prospects for process manufacturers, their team members and customers. In an era of increasing competition, customers are demanding excellence and speedier times to market. Agile and forward-looking organizations will greatly benefit from embracing Industry 5.0 with an AI assist that will improve safety, productivity and competitive advantage.
Andreas Eschbach is the founder and CEO of the software company eschbach, which helps production teams stay safe and work smarter through better information sharing and collaboration. Holding a degree in computer science, he draws his practical experience from leading a variety of international software consulting and implementation projects for leading chemical manufacturing companies, focusing on production, continuous improvement, EHS and maintenance. His company is a provider of manufacturing solutions and headquartered in southern Germany and has an office in Boston, Massachusetts.
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