In our global economy, disruptions in logistics—whether upstream supply chain or downstream delivery—can be detrimental to a business. Delayed part shipments can wreak havoc on manufacturing plans, and have ramifications that reverberate both down to the customer and across to other product lines. Errors in the logistics networks, equipment failures, parts shortages, customs delays at ports or border crossings, inclement weather, and even political disruptions can cause a domino effect across the factory floor, possibly affecting an entire business ecosystem.
Thanks to an advanced, artificial intelligence (AI)-based data and analytics logistics program, the manufacturer noted above was notified of the possibility of the shipment delay the day before, and was able to initiate a resolution, allowing the company to get ahead of the disruption. But it took diligence and trust in a new technology to create a better system.
By now, most companies in the industrial space are aware that information from their process and operations can help guard against failures, and make production more efficient. For example, Frost & Sullivan estimates that, on average, 35 percent of global automotive plants will be “smart factories” by 2025 meaning that automotive OEMs will need to spend 8 to 10 percent of their revenues on these new or upgraded facilities.