How Machine Learning Unlocks the Potential of Operational Excellence in Manual Operation

Delivering consistent and efficient operating performance is the key to achieving operational excellence and process safety. While the process industry faces the wave of the Fourth Industrial Revolution, many manual operations remain due to the difficulty and the uncertain cost-effectiveness of fully automating the process.

Companies have Standard Operating Procedures (SOPs) to guide the operators through manual operations and standardize the processes. However, these paper-based SOPs are occasionally outdated, not updated, and do not reflect the current most efficient way to drive the process. When procedures are not properly documented, plants rely on the knowledge of the most experienced operators, which results in:

• Operating performance may vary from one operator to another.
• Onboarding of new operators is difficult and requires great effort, and operators may feel uncomfortable and insecure.
• The safety of operations may be impacted.

In today’s highly competitive world and with operators expected to take on wider responsibilities due to labor shortages, the challenge is critical.

• What if your plant was permanently operated by your best operator, based on standard and optimal operating procedures? 
• What if you could extract this human experience and transfer it to all your employees? 
• What if these “golden procedures” were maintained electronically, providing live support to your operators?

This whitepaper describes an innovative approach to optimizing manual operations in the process industry: combining Distributed Control System (DCS) data and domain knowledge with the latest machine learning technology to visualize the actual operating procedures and capture the implicit knowledge of experienced operators. Through case studies, it also explains how operation managers, both experienced and new, IIoT/digital transformation leaders, and their colleagues can utilize this type of solution to identify best practices and improve production performance.

 

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