The manufacturing industry is in a bit of a pickle. Emerging technologies are coming at it from every direction, as digital transformation and integrated supply chains are being touted as the solution to all their woes. Industry 4.0, Logistics 4.0, AI, IoT, RFID, there are enough buzzwords and acronyms to make even the most seasoned production planner’s head spin. What’s a planner to do? As with so many areas of life, the key is to move one step at a time. See if any of the following five challenges apply to you, and if so, start by addressing them. Then, when you can see your way clear of that challenge, you’ll have a better understanding of what to address next for the greatest impact.
Remember that one part of The Wizard of Oz? The one where the wiz comes out from behind the curtains? How was that one little guy able to control everything from his perch back there, without anyone being any the wiser? That I can’t tell you, but I can tell you we’re getting closer to a 21st-century version with the continuing maturation of the Internet of Things (IoT). The emerging technology that powers the 4th industrial revolution, Industry 4.0, is giving us a glimpse of what it would have been like sitting back there, with a view into all the goings-on of our realm.
Let’s say you’re a homebrewer, and you’ve just finished drafting your recipe for a dry-hopped pale ale that you plan to brew in the coming weeks. If you’re like most people, you go to a homebrew supply site and order your hops, malt, and yeast all at once, plus some clean bottles for your brew to wind up in. This strategy works perfectly well, but as you go, you find that it leaves something to be desired. While your beer is fermenting, you have a bunch of bottles taking up unnecessary space on your floor; and by the time you’re ready to dry-hop (which involves adding more hops during the fermentation period), the ones you bought from the homebrew site are a little stale.
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.
Let’s picture a hypothetical. You’re a sales and operations planner at a global manufacturer, specializing in a high-end variety of widget that other global companies tend to order in large quantities. Your sales cycle is fairly long, so every time a member of your sales team closes a deal it feels like a major victory. Recently, you’ve closed one of your largest deals yet, meaning that a large quantity of deliverables need to be produced in the immediate future. This will mean leveraging your production facilities at their maximum capacity for some time (potentially resulting in some wear and tear on your machines that will cause slowdowns later), but, like they say, “make hay while the sun shines.”
In the past five to 10 years, real-time information has become a key value-added proposition for bolstering efficiency and decreasing waste in modern, digital supply chains. Businesses have used it to power more agile, responsive processes within their own value streams, creating environments that are primed for improved data-quality and easier analytics integration. The question remains, however, is this technology being utilized to its maximum effect, or are there still use-cases for real-time information that most businesses are failing to fully leverage? The answer is resoundingly the latter, as evidenced by these four surprising uses for real-time supply chain data.
Any production planner who has spent time working on non-clocked production processes can tell you that it presents challenges and hurdles that simply don’t exist on assembly lines or in other linear production processes. And yet, for some manufacturing outfits, non-timed production is the best way to maximize their machine and personnel resources while maintaining a relatively flexible and adaptable production environment. How do we reconcile the difficulty of scheduling production in a job shop with the obvious value that it presents for many businesses, and what can that tell us about the future of job shop scheduling?
Imagine you’re working in tech support, and you receive a call from someone who’s having trouble getting his phone to send and receive text messages. You try all of the usual tactics, asking the caller to turn the phone off and on again, etc., before checking to make sure that the phone is running the latest version of its operating system. The caller concedes that it probably isn’t, but as you walk him through the process of updating he continues to run into problems. “How,” he asks, “do I see what operating systems I am running?” “How do I access my settings?” “How do I get to the home screen?” It is only as you dive deeper into the rabbit hole that you realize that your interlocutor doesn’t have a smart phone at all, but an old rotary phone without the slimmest chance of ever accessing the internet.
Seasonality, which refers to regular, predictable fluctuations that recur year over year, has traditionally been a major factor in automotive manufacturing. Since car sales often spike in spring and autumn (when new models are traditionally released) and drop off in winter and summer, manufacturers can and do factor seasonal slow-downs and increases in demand (potentially including demand for new parts) into their production processes. With the rise of Industry 4.0 and the emergence of an increasingly global supply chain, however, the nature of seasonality is rapidly changing. Let’s take a look at how seasonalities operates in modern manufacturing.
It’s safe to say Big Data is here to stay. Since its introduction in the manufacturing landscape in the early 1990’s, Big Data has demonstrated its value proposition in the capacity for grouping, sorting, and analyzing large and complex data sets into executable actions, provides planners and managers the capability to apply predictive analytics and other forward-looking logistic strategies to increase the efficacy, efficiency, and cost-effectiveness of planning and production programs.
Big Data has since found a home working in tandem with other supply and manufacturing movements such as Industry 4.0, Advanced Analytics, and The Internet of Things (IoT). Alongside these technological developments and platforms, Big Data has helped companies gain increased insight and visibility into a number of critical planning and production functions such as forecasting, modeling, data analysis, and the implementation of integrated sales and manufacturing principles for a more streamlined production cycle.