Manufacturing teams used to manage the supply chain group. Today, in most organizations, the supply chain team manages manufacturing. The irony is that fewer and fewer people within the supply chain team understand manufacturing. Unfortunately, few have worn hard hats, safety shoes and calibrated a machine to run within spec. I feel lucky that I have.
As I work with teams to envision the new tomorrow, I find fewer people know the basic concepts of manufacturing planning–cycle inventories, freeze duration, slush period, bottlenecks and constraints. As a result, it is more difficult for the teams to see the swirl of opportunities that are on our horizon. Instead, many of these teams just accept manufacturing strategy as a constant. However, if we look at the current trends, I think that we have the convergence of new opportunities to drive a manufacturing redesign. It requires rethinking mental models. To do this, leaders need to be knowledgeable on both manufacturing and supply chain concepts.
Here are some opportunities that I see:
Service Parts. Last week, I spoke at a partner meeting for a large consulting company. Many of the partners in the room work on service part supply chains. When they asked about the current state of service-parts planning software, I asked, “Why are you not asking about the redesign of the service supply chain?” Today, using the Internet of Things, companies can sense equipment status and predict failure. We no longer have to plan maintenance based on the prediction of mean-time failure. Instead, we can sense the patterns on the equipment and be proactive about service. I also think that we can use 3D printing to manufacturer more and more of the parts in the field. Perhaps digital files can be sent to the local UPS or FedEx office, which they print using specialized printers and deliver it to the site of the equipment. As a result, we will have to stock fewer and fewer parts. And, the service supply chain can be redesigned to have less inventory and more uptime.
Let me give you an example. I live in West Virginia. The mining equipment in WV is located in remote locations that are hard to service. The equipment is at the heart of the operation. When the equipment is down, the work stops. Today, heavy equipment is equipped with telemetry that transmits signals frequently on the state of motors, oil and belts. Why can’t we sense these in real-time monitoring and provide a newly designed demand-driven service supply chain that senses equipment starting to fail and then stages equipment based on need? And, where possible print the parts in the field, on demand, as needed. I like the thought of having a bearing printed in Boone, WV instead of being stocked in Chicago and then flown into Charleston, WV to then be driven to the coal mining site. The time to service the equipment would be in hours versus days and the amount of inventory to provide the service would be greatly reduced.
Apparel. With the rising costs of labor in China, many apparel manufacturers share that there is only a 6% differential between sewing a garment in China or manufacturing in the United States. When the added costs of transportation and inventory working capital impacts are added, there is a solid logic to bringing manufacturing back to North America.
Mexico has become more attractive, and many companies are looking at alternative sourcing in Latin and South America. With every shift, we have the opportunity to redesign the value network to better sense and translate demand. The focus needs to be based on market drivers with a view on the total impact of the decision. I love the fact that we now have technologies that allow us to make the decisions based on total cost and impact on the Effective Frontier. The decisions on postponement, push-pull strategies and buffer inventory positioning are not always straight forward. The use of technologies like Llamasoft, JDA’s strategist and Solvoyo enable more advanced analysis than the first generation of strategic optimization technologies found in the Oracle and old Manugistics tools.
Medical Device. Today, implants roll around in the trunk of a salesperson’s car. It is called trunk stock. The inventory in the medical device industry turns at 3X a year. Many times, multiple devices are taken into the operating room to ensure fit. So, what if the patient could be scanned in pre-op and a custom device could be printed in the hospital? Need a new knee? Have it printed the day before based on your scans of the knee using the technologies and specialized substrates in the back room of the hospital complex.
Process Industry. Today, there are thousands of machines in all process manufacturers that emit signals based on programmable logic controllers (PLCs). The outputs of the machines are not used in a comprehensive manner. What if we had a cognitive learning engine with a rules-based ontology sitting on top of these PLC inputs to help us schedule the line? The current planning systems assume that production should be scheduled based on predictive maintenance programs based on mean-time failure and recommended maintenance intervals. However, if we could directly sense the patterns in the equipment could we do a better job of scheduling maintenance and planning production? I think so.
Also, order streams are recorded and processed in batches. As this happens in the process industries, companies lose visibility of flows. Let me explain. Is customer X ordering more or less of product Y than expected? What is the pattern and how does this tie to market drivers or past demand? Today, companies can see volume, but they cannot see patterns. I think that the combination of cognitive learning for planning along with the use of signals through the Internet of Things has the opportunity to usher in a new era of process manufacturing. I envision a greener process with less inventory and lower costs. I was speaking to one manufacturer the other day that told me of a factory that has two employees. The operators sit at home and run the factory in their PJs in front of their terminals in their living room. Quite a different story than the large teams I used to manage in a factory.
The redesign is exciting. The potential is endless. It requires the adoption of new mental models. We are currently doing research on this topic for a July report. If you fill out the survey, and share your story, we will be glad to share the results.
We would love to hear from you on where you are on adapting your manufacturing processes to adopt these new techniques. And, as always, if you fill out one of our surveys, we will keep your responses anonymous, and only share the data in aggregate.
I look forward to hearing your story.