Submitted by Andrew Waycott, COO & Co-Founder at TwinThread
Just-in-time manufacturing has transformed most manufacturers and their respective supply chains - generally, in a very positive manner. However, of all the manufacturing developments, just-in-time manufacturing may be the one that presents the most significant challenges, from an operational efficiency standpoint. As a reactionary process methodology that focuses squarely on production needs instead of production optimization, organizations that subject themselves to this approach will be forced into a perpetual state of catch-up or hurry-up and wait.
What’s more, since all of an operator’s attention is allotted to output needs, there is little to no consideration being invested into process optimization and increased efficiency. For this reason, it takes a substantially lengthier period of time to identify impactful advancements, and even longer to dial in the process - if that ever occurs. All of this adds up to a culture of instability, uncertainty and variability. Without a continued augmentation of control over your processes, not only will you suffer from an inability to improve, but you’ll see sporadic performance when it comes to efficiency.
You’ll have no method for (accurately) gauging what the quality, uptime or throughput of a particular production cycle will be. It goes without saying - that’s a nightmare. Fortunately, this pain hasn’t fallen on deaf ears and no operation needs to endure this struggle of uncertainty any longer.
Through the real-time insights that predictive data analysis affords, organizations are emboldened to clearly uncover where their assets’ sweet spots are and how best to exploit them to an advantage. Imagine having a solution that informs you of the realities of your operations, on a given day and product run, as they are happening. With machine learning providing data-driven insight, your operators can realize their problem-solving potential in an expeditious fashion, allowing them to continuously implement impactful tweaks and changes to process that will optimize all operational efforts.