Digital Transformation Impacts Manufacturing Innovation and Supply Chain

Digital transformation professional services companies provide value to owner/operators and manufacturing companies. But their services are often expensive. I have done some work on platforms such as MIMOSA’s OIIE (which is still in development) that are designed to use standards and interoperability to help these customers reduce their expense and dependence on these firms.

It’s sort of a “good news, bad news” thing.

At any rate, the PR firm representing Cognizant contacted me toward the end of December with an opportunity to interview an executive. The purpose of this interview would be to update me on the company and talk a little about digital supply chain, workforce, and other manufacturing innovation topics.

Anxious to get something done before the end of the year (billable hours?), they even offered times between Christmas and New Years. Prasad Satyavolu, global head of innovation, manufacturing, and logistics practice, talked with me shortly before Christmas.

When I laid out the conversation on a mind map, the map was huge. So I thought about it off and on for the past couple of weeks. These thoughts reflect about half of the conversation. There is a lot to think about.

Cognizant was a very familiar name, but I couldn’t place it. “We are familiar with SCADA and plant floor,” Satyavolu told me. “We acquired Wonderware’s R&D operations. In fact, we still work with Schneider Electric. We also work with Rockwell Automation.”

Core Manufacturing services include:

• Transportation/Material Handling

• Process industry

• Energy/Oil & Gas

• Aerospace (some)

• Automation

• Utilities/Smart Grid/Smart Meters

When Cognizant evaluates a customer’s processes and lays out a plan, it includes everything from incoming supply to manufacturing to shipping to customer. The demand and supply chain.

One opportunity Satyavolu sees considers more instrumentation leading to additional sensing of movement of materials and workers in order to capture better decisions and enable efficiencies.

Then consider the confluence of changing workforce and technology. “Consider reality on shop floor. 5-10 years ago a maintenance engineer listened to a machine, diagnosed the problem, and fixed the machine.

The next generation doesn’t have that knowledge. Today the time to fix has gone from 15 minutes to 4 hours. How can we tackle knowledge gap? Further, is the next generation even interested in this sort of work?

Looking ahead, by 2025 we will be short 8 million people with manufacturing skills. How does this impact global mid-sized companies? How can we further leverage robotics to help solve this problem? Would robotics technology even make the work more attractive to a new generation of workers from the world of gaming and drones?

Huge opportunities exist with visibility outside the plant to planning and execution. It’s the Amazon effect—velocity so high that you almost have to produce on demand. Predictive maintenance systems enable managers to manage schedules and demands. This leverages infastructure such as cloud, digital technologies. These improve scheduling, reschedules lowering carrying costs; aids risk management / mitigation; global organizations bringing parts from around the world, global demand/supply increases uncertainty.

On shop floor, plant has fixed schedules / horizons. Scheduling systems and a lot of modeling bring stability and improve effectiveness. You can simulate production quickly, get status of inbound parts, changes in demand side, sync with labor requirements. With better scheduling, you get better visibility—you can save 12-13% of costs with sync. You can track supply chain, transportation, and change schedules in advance improving risk management.

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