In the past few years, sustainability has become a topic of considerable importance throughout the automotive industry. As the automotive supply chain becomes increasingly globalized, businesses are now more than ever faced with the Herculean task of managing not just the logistics and costs associated with a complex web of global suppliers, but with the environmental impact and long term sustainability of the associated businesses practices. While this process is often daunting, it has grown in importance to the point where manufacturers ignore it at their own peril. Even beyond supply chain considerations, many businesses are finding that discussions of sustainability bring up questions and dilemmas that they’ve never faced before, from deciding on acceptable trade offs between sustainability and profitability and uncovering areas where sustainability increases profitability, to developing new KPIs for managing vendors and suppliers.
It’s still about a month until Thanksgiving, but you may already be deep into the planning process for the big event. Some of your friends and family are flakey, so you won’t have a full list of RSVPs until much closer to the holiday itself, meaning that when you sit down to sketch out what dishes you’ll be cooking and what ingredients they’ll require, you’ll have to use a combination of confirmed and projected attendees. For some dishes, it might be easier to wait until a few days before Thanksgiving to get the necessary ingredients, but you’re worried that your nearby grocery stores might run out of a particular brand you like if you wait too long, and there are some items that need to be purchased well in advance because they need to be stale or overripe before they can be used, like bread for stuffing or bread pudding.
Let's say you're an OEM, with a sleek manufacturing space and a sophisticated, technologically cutting edge process for creating a particular automotive part. But you have a problem: At this point, your incredibly sophisticated production techniques aren't not being complemented by an equally sophisticated, multi-level approach to production planning and resource scheduling. This results in a disconnect between the high quality of your products and your ability to maximize capacity and meet customer delivery requirements. How can you build towards a production planning workflow that complements your product and fulfills your business goals?
IT pioneer and philosopher Ted Nelson, who coined the term hypertext, once famously said, "The good news about computers is that they do what you tell them to do. The bad news is that they do what you tell them to do." Historically, in the automotive supply chain, this couldn’t be more true. New technological developments like early computerized workflows and simple process automation were hampered by information silos and integration issues not because the technology lacked sophistication, but because they still had to be told what to do in very specific ways.
Imagine you own and operate a pin factory at the dawn of the Industrial Revolution. One day, you come in and announce to your workers that you’ll be implementing steam powered machinery into your production processes, completely reimagining many existing workflows in the process. How do you think your employees, especially those involved in planning out production workflows, are likely to react? Some of them might be excited or intrigued, certainly, but many others are likely to meet the news with apprehension or even distrust. After all, they were doing just fine making pins by hand all this time.
Here at the flexis blog, we’ve spoken on more than one occasion about the inherent difficulties of job shop scheduling and the significant value added potential of developing a smart, digitized workflow for non-timed production planning. Because there is no known algorithm that can efficiently solve the problem of non-clocked production under all circumstances, the pen and paper production planners of the world are almost certainly failing to optimize their machine and personnel usage in job shop production settings. On the other hand, the path to optimal planning can appear dauntingly complex. To help you as you navigate these hurdles, we’re happy to present a case study on ENisco’s successful attempt to master the job shop problem.
According to McKinsey’s estimates, the rise of the Internet-of-Things (IoT) will have more than a $11 trillion economic impact within the next 7 years. Much of this value will come in the rapidly evolving world of connected consumer goods, such as the internet-enabled products that make up the modern smart home, but the impact will also be felt widely in a number of industries, from health care to natural gas production to, of course, automotive manufacturing. We’ve spoken briefly on this blog about the application of IoT devices for tracking inventory usage and traffic patterns, but what impact will this explosion of connected devices have on factory production processes themselves? More to the point, how can you leverage them into meaningful value propositions within your business’ existing workflows.
Imagine you’re living in a smart home. One evening after work you decide to drive to the grocery store to pick up snacks and drinks for an upcoming party that you’re hosting. When you take the road to the market rather than your usual route home, your car sends a notification to the appliances awaiting you at your house. The refrigerator, sensing that you’re low on milk, sends a reminder to your phone to pick some more up. Your dishwasher, tracking your detergent usage over time, estimates that you will run out before you next go shopping, because you usually wait at least a week between trips. Lastly, your car sends a text alert to your spouse, who might remind you of your guests' snack food preferences or other salient details.
Although automotive manufacturers have been hearing for years that Big Data is the next big thing, studies often show that executives, not just in automotive but across many different industries, fear that their organizations aren’t ready to take advantage of the new advancements in analytics. Big Data analytics can and will be a huge value-added proposition for companies hoping to stay competitive in the world of Industry 4.0, but it’s true that reaping the benefits of new technological insights often requires significant changes in workflows and IT infrastructure. Luckily, these changes are often not as daunting as they first appear. Here are a few suggestions for getting the most out of your advanced analytics.
Murphy’s Law states that whatever can go wrong, will go wrong—and nowhere is that more true than in the world of global supply chain management. Risk is simply a fact of life in almost all business spheres, but automotive industry manufacturers in particular frequently deal with incredibly complex supply streams that face a near-certainty of disruption. Managing complex relationships between suppliers, shippers, and production processes can lead planners to the brink of numerous potential pitfalls, but, luckily, in the era of Industry 4.0 there are more tools than ever designed to alleviate the pain points of the past.