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NOV-DEC 2018

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16 INTECH NOVEMBER/DECEMBER 2018 WWW.ISA.ORG Instead of a custom Industry 4.0 strategy based on the existing processes and system landscape within a compa- ny, many have a checklist of technologies they want to use, whether their processes require them or not: IoT/IIoT, AI/ ML, mobile devices, augmented reality (AR)/virtual reality (VR), cloud, etc. First steps for a successful implementation Your experienced workforce is critical to identifying both low-hanging fruit and your biggest pain points. l Map every step in every process and every system that is used. You need to understand what each step or system is used for, what is done, why it is done, and how it is done. l See what works well and which standards are used. But more importantly, see what is not working and which stan- dards are not used. Common low-hanging fruit Plant communication: Digitize paper-based plant data into dashboards to transform existing analog data into real-time information, so you can use this knowledge. This becomes a powerful asset for artificial intelligence (AI) and machine learning (ML) implementations. Dashboards on screens, laptops, and mobile devices not only let you make data- driv en decisions in the moment, but also enable you to see what works and what does not. Constant process optimization: Using collected data to drive plant optimization is not new. Data-driven methods like Six Sigma or Lean in combination with a data historian are a match made in heaven. A historian can provide ample data for your measurement and analysis phase, allowing you to quickly perform a comprehensive root-cause analysis and review sustainability. Real-time optimization applications are available, but the complexity, skills required, and cost in volved mean they are not suitable for all situations. Interfaces between systems: Many companies have a variety of systems in use, such as ERP, SCM, CRM, QMS, LIMS, WMS, MES, DCS/SCADA, and HRM systems. But most are isolat- ed where data and information exchange is rudimentary— paper-based or via text email at best. Start creating your company's digital thread by setting up interfaces based on standards like OPC-UA, Message Queuing Telemetry Trans- port (MQTT), Rest, or Open Database Connectivity (ODBC) in combination with ETL (extract, transform, load) or ELT (extract, load, transform). Predictive maintenance, or using machine learning to produce a maintenance model, is not a short-term project. In fact, one company admitted in its 2018 keynote that its machine learn- ing project was yet to produce a working model, even after three years. Its machines are scheduled for replacement in two years. Do not jump into a machine learning solution if you can- not solve the problem without it. Leverage your employee's experience first—mechanics often "know" whether their machines are running well, because they have a model in their head of what they need to keep an eye on. Tap into their experience and monitor what they suggest. nization and across its value chains. It is about the human ele- ment and how our workers can truly add value with their cre- ativity and innovation. This understanding of Industry 4.0 has gained significant traction since I first became involved in 2014. New process industry use cases Example use cases from the process industry (Covestry, Lonza, HPE and Texmark) were highlighted in several key - notes in the recent Industry of Things World conference in Berlin, illustrating how conforming to ISA-95 can quickly bring benefits from enhanced data collection. A few use cases showed how mobile devices brought real-time data into the field when checking critical assets, instead of keep - ing that information locked away in a control room. Others showcased how digitized dashboards improved on paper- based communication channels. All of these improvements were to processes. The benefits were realized by following the Industry 4.0 principles of improved communication and open information sharing. Industry 4.0 has a future in the process industry Until now, Industry 4.0 did not clearly show how it could benefit the process industry, because the focus appeared to be on the technology and the hype around how many jobs would be lost. However, Industry 4.0 is about establishing an active collaborative network, both within organizations and throughout their value chains: people and technology con - nected by digital threads and limitless information exchange. The process industry is full of hierarchical organiza- tions with isolated operational silos and information stored behind "locked doors." The way forward is clearly a solution- oriented network of people, tools, and shared information across boundaries, supported by the process industry's ex- isting standards and technologies. Implementing Industry 4.0 Why so many projects fail In my experience, organizations do not start at the begin- ning, by understanding their processes. Instead, they start with reports or dashboards already in mind. But the solu- tions selected to deliver those outcomes rarely survive the first contact with reality. These projects fail, because they fall into a constant cycle of modifications and rebuilds, as each step in the processes throws up unforeseen issues, causing delays and increased costs. PROCESS AUTOMATION Mismatch as a result of not starting at the beginning

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