Seeing beyond the fog

If you are a manufacturer, you are probably swamped with information from plenty of channels regarding Smart manufacturing and Industry 4.0. There is no doubt that Smart manufacturing is emerging as a must-have capability in the future for manufacturers. We all know that getting there will not be a step-change process. In my opinion, you do not flip a switch to transition to a smart factory. The process needs to be gradual.

The four foundation pillars

This brings me to a question that many Manufacturing leaders ask: What areas should we start focussing on as far as our manufacturing operations go? After all, through their experience, they know that they need to start building foundations in those areas. Based on my experience, the following are the four areas they need to focus on:

• Systems Connectivity
• Automation
• Visibility
• Analytics

In the subsequent section’s description of each of the pillars, you will see a “start by” team. This is not a detailed description of how you can build the capabilities in that foundational area but a hint to get you to start thinking. Evaluating each area and creating a roadmap for the four areas is exhaustive.

Understanding the foundational pillars in detail

Systems Connectivity

A key aspect of Smart Manufacturing environments is that all plant equipment will communicate with each other with a central control system, which will then integrate with systems above them… to an enterprise system-level connectivity.

Start by understanding your systems, then connect between systems and evaluate gaps. Today’s cloud architectures make connectivity between systems much easier via application programming interfaces (APIs). For example, securing IIoT to a Manufacturing Execution System (MES) can help avoid unplanned downtime, and connecting both to enterprise resource planning (ERP) provides immediate visibility into asset status throughout the business.

Automation

As repeatedly mentioned in my posts and articles, Automated factories do not mean Smart Factories. Automated factories, though, are essential to developing Smart Factories and are a foundational pillar.

Start by evaluating your current Production technology (which differs from production information systems). Production technology goes beyond having physical robots in your Manufacturing lines. In addition to automating mundane or error-prone tasks like labeling or counting, production technology can accurately inspect products and record scrap reasons. The software can automate paper or email-based business processes with electronic workflows.

Further, robotic process automation (RPA) can then automate repetitive workflow tasks, coupled with machine learning, continually improving the process over time. For example, on detecting non-conforming products or materials, the system can trace that source material back through the production line and to a place where it can be automatically rejected or marked for removal, streamlining the approval process.

Visibility

Just like automation in Manufacturing, Tracking inventory and processes isn’t a new concept. However, leveraging the digital thread of the resulting electronic “paper trail” will be fundamental in intelligent methods and smart factories.

Start by evaluating what your current tracking capabilities are like. Are you in real-time? If not, how “real-time” do your real-time capabilities need to be? What Business Intelligence tools do you have internally to gain that tracking capability?

Analytics

Since the technology behind Smart Manufacturing, thanks to cloud technology, will be accessible to companies of all sizes, the real differentiator in the Smart Manufacturing domain will be analytical capabilities.

Real-time manufacturing intelligence helps to report and visualize critical key performance indicators (KPIs) for quicker, more confident decision-making. But the key is contextual analytics -Powerful analytics drive informed decision-making from asset performance on the shop floor to business performance on the top floor and maintain detailed historical records for future trend analyses.

Combining the above capabilities in a platform and artificial intelligence (AI), the resulting platform can discern and report patterns in the data humans cannot see.

And to be very realistic-Unlike AI in the movies, the platform provides humans with better data to make smarter decisions.

Start by leveraging simple descriptive analytics. True and sustainable analytical capabilities always start small. Prepare a roadmap to get to more advanced analytical capabilities.

Conclusion

As mentioned above, evaluating each area and creating a roadmap for each of the four regions is an exhaustive process, but it is something that you need to get started on as soon as possible. The evaluation, gap analysis, and roadmap will differ from one industry to another and may vary even between players in the same industry. As I consistently say:

With technology becoming a commodity, what will provide you an edge is NOT what technology you implement but: Building the right technology portfolio and integrating it effectively with your unique business nuances.