Industry 4.0 Offers Manufacturing Improvement Opportunities

Five key competencies of digitally mature organizations serve as a good base for making sure you’re prepared to take advantage of the technologies available.

For decades, manufacturers have driven continuous improvement and quality management programs based on Lean, Six Sigma, or overall equipment effectiveness (OEE) philosophies. Although these provide a solid foundation for operational excellence, a new wave of approaches driven by Industry 4.0 technologies is offering unparalleled improvement opportunities.

Digital maturity correlates with competitive advantage in time to market, cost efficiency, product quality, and customer satisfaction. But what does it take to be digitally mature? Emerson’s analysis of top-quartile industry performers provides a good framework, outlining five competencies of digitally mature organizations: automated workflow, decision support, mobility, workforce upskilling, and change management.

Competency 1: Automated workflow

Many manufacturers run their production work orders, preventive control plan, or raw material workflows by compiling information from a manufacturing execution system (MES), warehouse management system (WMS), and a number of other information sources and formats such as Excel spreadsheets.

But digitally mature manufacturers take this to the next level, using automated workflows to orchestrate different systems, people, and machines to run the show. These workflows pull information from disparate systems, assign tasks to people, respond to events, and push information back into the systems. Think of an orchestra conductor—he or she doesn’t play an instrument but instead instructs dozens of people to play their instruments at once…that’s what workflow orchestration is all about.

Competency 2: Decision support

Digitally transformed organizations will usually leverage at least one of two types of decision support:

• Automated decision support, where decision support is embedded into the workflow so decisions can be made in an automated fashion. The workflow could contain a decision matrix that is able to make decisions based on data and decide what actions it should take, what needs human intervention, and what doesn’t.
• Expert third-party decision support can take multiple forms. It could be an external consultant working on a project, an embedded expert within the business, a remote expert who can access your data when required to lend advice, or internal highly skilled domain specialists who have analytical skillsets to be able to make sense of data.

Competency 3: Mobile and remote accessibility

The next logical step of automated processes and decision-making is in access—that is, how you and your staff interact with physical and IT/software systems to carry out your work.

• Mobile technologies are being increasingly integrated into systems—including OEE systems, paperless quality management systems, and maintenance management systems—to create the connected worker. This capability allows people to move freely around the factory floor and focus on other core tasks such as continuous improvement, tending to exceptions by notification rather than having to monitor systems and machines.
• Remote accessibility refers to the ability for managers to review metrics remotely, in real time. It also refers to domain specialists being able to connect remotely to your system to see what you see and resolve faults.

Competency 4: Workforce upskilling

As more data flows in from different systems and devices, manufacturers will do well to harness automated workflows to orchestrate people, systems, machines and processes, and take smart action from this data.

Every digital transformation initiative should be centered on workforce training and change management.

When it comes to employees, the real challenge is upskilling operators in the areas of continuous improvement, preventive maintenance, and their understanding of how the whole line operates, rather than just one isolated machine.

For managers using automated workflows, the skill shift lies in refocusing their managing efforts from asset management toward deeply managing their workforce and the process or workflow itself. Managers will need to be skilled in data analysis and subsequent decision-making to optimize workflows.

Competency 5: Effective change management

Though workforce training plays an important role for digitally transformed organizations, change management as a whole should not be overlooked. As noted in CIO magazine “43% of 4,500 CIOs surveyed for the 2017 Harvey Nash/KPMG CIO survey cited resistance to change as the top impediment to a successful digital strategy.”

Effective change management involves consistent stakeholder engagement throughout the project, cross-department collaboration, and seeking input from people who will ultimately be running the new technologies or processes—they’ll have the best ideas, and their uptake of the change will either make or break the project.

Conclusion

Quality control and operational uptime are not new problems, but industry 4.0 technologies such as automated workflows and decision support offer manufacturers a new way to solve them. As more data flows in from different systems and devices, manufacturers will do well to harness automated workflows to orchestrate people, systems, machines and processes, and take smart action from this data.

Written by:  Kim Fiddaman, Senior Consultant at Nukon, for AutomationWorld.