Even manufacturers themselves may sometimes forget how tremendous the global manufacturing sector really is. Manufacturing in the U.S. on its own, for instance, would be in the world’s top 10 economies. Because this sector encompasses so many different businesses with so many different missions and products, it’s easy to prove or disprove almost any prediction. Sure, someone among the incredibly diverse array of global electronics producers is probably using voice activated AI in their plants—just as someone else is probably bucking every emerging trend by continuing to eschew digitization and connectivity. Still, as general trends emerge, it can be helpful to identify and understand them. To that end, here are some predictions for the world of global manufacturing in 2020.
In our last look at Logistics 4.0 statistics, we discussed 5 that we feel will help define the shipping and logistics sector in the coming years. Today, we’re going to add to that list with 5 numbers we feel might be getting short shrift in coverage of this arena. Logistics is undergoing a collection of disruptions that seem to have hit out of the blue. There’s a seeming tsunami of dissatisfied customers, rising fuel costs, and global weather pattern changes, to name but a few. In order to respond appropriately, the shippers of the world have had to pivot, fast. Many are choosing to dive headfirst into the emerging world of Industry 4.0 technologies that promise to help predict at least some of these disruptions far enough in advance that alternative plans can be set in motion. Among the technologies seeing increasing adoption are AI, machine learning, RPA, and IoT. These technologies, combined with intelligent deployment tactics, are already having a big impact on the global supply chain.
Logistics 4.0 is an offshoot of the larger trend in manufacturing known as Industry 4.0. Think of it as being to the supply chain what Industry 4.0 is to the factory, and you’ll begin to see the potential for massive disruption (of the good kind). As such, there is considerable overlap in the technologies at play. For example, the same IoT sensors that are revolutionizing preventative maintenance on the production line are also revolutionizing how the purchasing department determines what supplies to order. And the ability to automate production processes is being mirrored in the way those orders are being placed and the shipments themselves are being handled when they arrive. With the arrival of smart pallets, shelves, trucks, containers—even entire warehouses—logistics providers are able to create complete transparency up and down the value chain.
Let's say you’re a bartender in a sleepy neighborhood pub in your city. Your place might reasonably be called a dive bar, and you have a handful of regulars who come and order basically the same drinks week after week. As a result, your ordering process for restocking the bar is extremely simple. With little variation, you expect to go through predictable quantities of gin, tonic, bourbon, and cheap beer every month, and you’ve simply placed a standing order with the local distribution company to restock these things in the same quantity every so often. Life is pretty easy.
Let’s say it’s the day after Thanksgiving, and you’re trying to see how far you can stretch your leftovers. You take a good hard look at the fridge, where you note that given the amount of turkey, some mashed potatoes, some cranberry sauce, etc., you could probably put together another 6 person-meals for your family of 5. One of your family members, however, is a vegetarian, which means that any meals you put together for them can’t have any turkey or gravy. As such, they’ll need additional yams and mashed potatoes, which affects the proportions of the other plates that have to be assembled.
Lean manufacturing is a topic of choice these days. Discussions abound on everything from what works and what doesn’t, to how to make what’s not working work for you, to how to implement each individual segment of a lean architecture in a particular niche of the manufacturing world. That’s not our goal today. Instead, we want to cover one specific piece of the lean puzzle—every part every interval, or EPEI. We want to ensure you have a clear picture of this methodology, what it is and isn’t, whether it’s something you should consider implementing at your factory, and, finally, how Industry 4.0 is affecting its place in the value chain. Many of the issues addressed below are applicable to lean manufacturing more widely, so you can take the information presented and apply it to your situation and see how emerging technology might help your bottom line.
All the way at the far end of the supply chain, when an automobile reaches its end consumer, it looks like they’re buying one large item. But automotive manufacturers know differently—they know that each car on the road is really comprised of about 20,000 different parts, and all of them had to come from somewhere. After being sourced, they had to be stored, allocated for various production plans, brought to the production plant, and assembled into a road-worthy vehicle that someone could drive off the lot at their local car dealership.
Demand forecasting plays an important role in manufacturing. That fact isn’t changing; what is changing is how it’s done. Whereas in the past, forecasting had an aura of magic about it, relying heavily on the intuition and experience of the planner doing the forecasting, today it’s largely a data-driven practice. Before Industry 4.0, historical data was combined with gut feelings to produce a sort of crystal ball-like prediction of what the future held for the company in terms of demand and buyer behavior, and by extension what the company should focus on producing. Everyone basically crossed their fingers and hoped for the best. Post-Industry 4.0, this has changed dramatically, with a heavy reliance on advanced predictive analytics being fed data from IoT sensors deployed throughout the supply chain.
We’ve all been there at one point or another: you’re scheduling production for a large, complex item like an automobile in a plant that produces multiple different models. Your materials and capacity are relatively well synced, and your plans for the rest of the week or month seem pretty stable. Then, all of a sudden, a huge rush order comes in from an important client. All of a sudden, you're scrambling to allocate the materials and capacity necessary to slot this order into your existing plans. You pull resources from one order to give this one the resources it needs, but that has a complex ripple effect through your ordering flows; by the time you’re done reworking the schedule, your production plans are confusing and far from optimal.
Transparency is at the heart of both Industry 4.0 and the sales & operations planning process. Without visibility into every aspect of a supply chain, planners have no way to know for sure how something they do today will impact another department or team in the months to come. With visibility into those teams’ processes to see where the overlap is, they can see clearly how each move they make will impact the rest of the company and can better ensure that the entire value chain is protected from non-compliance. This may look different for production planners and operations managers, as each has their own priorities and needs. different needs. It can also look different at each stage of the plan from the same department, but the bottom line remains the same—visibility into the planning process is key to successful implementation.