Insurance is an interesting business. Just about everyone has one or more insurance products and most of us hope to never use them, or at best, use them sparingly. We are either mandated to have them or subscribe to them to hedge against risk, a structure fire, an accident, a medical issue. All pose significant financial burdens when left unprotected. Many types of insurance create incentives to help you lower your regular contributions; alarm systems, discounts for safe driving, or lower premiums for not smoking. While these are certainly beneficial to us as consumers, they’re offered to lower risk for the insurer, decreasing the likelihood of paying claims. In many cases we bear the cost of these programs that help them, and us, lower risk.
It’s curious then that so many in the industrial space expose themselves continue to incur the risks of not putting these systems in place that can detect or prevent failures. Even more troubling is that a significant failure is a collection stretching across numerous insurance types when in the context of personal products. Poor equipment health leads to lower production standards and higher costs. Failures may take equipment out of service for an extended period like a fire or accident would with our home or vehicle. Why do we take such risks in the workplace that we would be far less likely to take at home?
When insurance is being underwritten several factors are considered. Higher risk either incurs a higher premium or is not offered coverage because they know the probability of an incident requiring a claim or payment is higher than those with lower risk factors. Applying proper data models and maintenance procedures is the same concept. If you know where the risks exist and you take mitigating action to identify and lower their ability to occur, you increase the likelihood of preventing problems. Having a comprehensive set of knowledge that shows how defects or failures present themselves, identifying the appropriate technology to monitor for that pattern, and applying it across various equipment will help improve your underlying OEE metrics.
The path is there for you to take. It does require work and does not fully remove risk. However, the knowledge to guide you through the journey and lessen the possibility of significant failures or wasted resources on ineffective methods is at your fingertips.
