A.I. and Computer Vision Are Your Best Defense Against the Coronavirus and Other Pandemics
While production disruptions in China have received the most attention with over 75,000 reported cases and 2800 deaths, factories are also being impacted in Japan and South Korea. Together the three East Asian countries represent 38% of global manufacturing.
In the last week, major outbreaks have been reported in Northern Italy, a major manufacturing hub for Europe. There are growing concerns that manufacturing in Germany and France will also be impacted as the number of confirmed cases grows so quickly.
Today’s global supply chains are much more fragile than in the past. When I began in supply chain in the 1960s and 1970s, there was a preference to build in safety stocks into inventory planning and source locally whenever possible. With the advent of Lean based on the Toyota Production System, the focus changed significantly to a just-in-time philosophy. The goal was to bring parts into the factory at the last possible hour and day. Running parallel with the growth of Lean is the obsession to chase the lowest global labor costs – a practice known as labor arbitrage.
The Coronavirus (technically designated as COVID-19) has created a shock to global supply chains. The first reaction of supply chain professionals would typically be to jump on the first flight available to get on-site at their suppliers. But travel of all kinds is now considered a high-risk proposition.
Even without a pandemic supply chain shock, site visits to distant and off-shore suppliers have major limitations. Suppliers are well versed in how to put on the best possible face to their customers’ sourcing teams when they show up on site. The problem is obvious: once the visitors depart, the suppliers revert to their normal operations, which may not be at the level needed to support their customers.
A much more effective remedy is to use artificial intelligence and computer vision to create a system of 24×7 monitoring and alerting system. Unlike an occasional and planned site visit, computer vision never stops watching and analyzing areas of interest. Unlike a passive/dumb camera system, there is no need to go back and review hours of video coverage. Smart cameras use algorithms to continuously monitor operations, and can even send alerts when they identify production, safety or compliance issues.
An example of using computer vision would be to monitor a supplier to verify that a production line is actually running for an entire shift and that a set number of workers are active in the production area. Alerts can be created to flag when the line stops for a given number of minutes and when workers are missing from planned staffing levels.
Another example would be to monitor for process violations, such as skipping a testing station. When a violation occurs, an alert would be created in real-time. Experience has shown that such monitoring will almost always result in improved process adherence and processing time efficiency. Trend analytics can also serve as an extremely valuable input to joint continuous improvement efforts. Typically, these activities are done episodically and in person. Frequent international travel is not only expensive from an out of pocket cost perspective, but can have a significant impact on productivity and morale when it becomes a monthly or even quarterly ritual – especially when team members are forced to leave family and friends behind to make these trip. Imagine even cutting the number of required trips in half this year! There is a continuing trend to move manufacturing from China to Southeast Asia, Mexico, and back to the United States. There is also an increasing likelihood that Corona-like epidemics and pandemics will no longer be Black Swans. Both of these trends make it very timely to deploy an A.I.-based computer vision monitoring and alerting system.//php comments_template(); ?>