Updated: Dec 17, 2019
Imagine you have a light bulb.
Imagine you have a light bulb. All light bulbs have a set lifespan. When would you switch out the bulb? The answer, obviously, is when the light bulb goes out because it has reached the end of its life.
Now think about throwing out a perfectly functioning light bulb and buying a replacement. To most everyone, this makes no sense and feels utterly a waste.
However, such an act of negligence is common occurring in the manufacturing industry.
When OEMs outsource their costly tooling to contract suppliers, the tracking of these assets and their utilization rates become, at the very best, difficult, and at the very worst, impossible - a situation referred to as the “Blackbox”.
Surprisingly, a lot of OEMs still rely on a manual data collection method from their suppliers to manage their tooling worldwide. Without automated data, it is impossible for OEMs to accurately benchmark their tooling utilization rates across plants, suppliers and regions.
What if you can automate your manufacturing data? Have them analyzed by an algorithm, and visualize them into KPIs?
Are your tooling being underutilized?
Since the utilization rates of tooling remain unknown to both OEMs and suppliers, OEMs regularly retire their tooling prematurely. Such actions have significant implications on tooling costs in the long-run.
Another common instance among OEMs is the considerable number of back-up tooling collecting dust in inventory. A world-class cosmetic OEM manufactures its seasonal products for only a few months every year. As a result, tooling used to manufacture these products are stashed away for the remaining duration.
The problem is, every time they take out these tooling for production, no one knew whether they should be retired or kept for further use. More specifically, no one had kept track of the utilization rates of these tooling. This leaves OEMs helpless, with no information on when, and how, many new tooling need to replace previous ones.
This is exactly the “Blackbox”.
How can OEMs overcome it?
OEMs must track each and every one of their tooling through automated data collection. Such practice will allow OEMs to know which of their tooling are being underutilized, as well as providing justification for the purchase of new tooling.
With maximized utilization of tooling before retirement, OEMs will be able to reduce the number of tooling and cut annual tooling costs by an average of 5% year-over-year.
Stop throwing out your light bulbs before they are finished, let alone your costly tooling. Global OEMs have been taking the utmost care of their tooling with the help of an automated tooling data analytics system. To learn more, read this case study with Samsung Electronics or talk to our experts directly.