This is my opinion or OP-ED as they say.

Could the two Michigan dam failures have been prevented? Could the flooding of the City of Midland have been prevented? Was it seen by the dam owners and the city officials as a crap shoot with the odds in their favor because it has been a few hundred years since the last time eight inches of rain fell?

For city infrastructure to operate properly, it is no different than manufacturing infrastructure operating properly. It will improve the bottom line.

The global industrial process intelligence firm Industrial Info Resources has reported that unexpected manufacturing outages have soared in recent years.

This is quadruple the number of outages, and 2020 has not started out much better. In fact, based on incidents in North America in February alone, the trend seems to be continuing, if not getting worse.

Business reporter Laura Sanicola of Reuters noted in a recent article in Plant Services, that insurance costs facing U.S. manufacturers are escalating. Production is at an all-time high with "increasingly complex operations running full-tilt" and many are postponing planned maintenance downtime to try to boost profits.

The production of products, be it to drive industry or to meet end-user consumer demand, will continue to push America's aging and "increasingly complex" infrastructure to its limits. This trend is raising concerns among many in industry and government (federal, state, and local) to ensure both safe operations of these facilities and protection of the community and surrounding environment. When looking at the alarming number of incidents and the reports of operators deferring planned shutdowns for maintenance, is it really a surprise that we are seeing so many avoidable incidents?

After 20 years of technical innovation and giant leaps in predictive sciences, one truth is apparent, we still have a lot of work to do to prevent unplanned shutdowns. It is dear that there are many factors at play in this "unmitigated spike in catastrophic incidents" equation. Much has been written on key contributors such as the aging infrastructure (particularly in North America), the rapid retirement of and overall downsizing of skilled maintenance and asset reliability professionals. and the huge backlog of work orders that many maintenance teams face. It is this backlog issue that frustrates so many, where maintenance teams are overwhelmed with work orders stacked up in their Enterprise Asset Management (EAM) or Computer Maintenance Management Systems (CMMS). There appears to be little or no information available to prioritize task criticality or risk to business, plant, people, and the environment if that work is not done.

Our current dichotomy is that on one hand, we have Artificial Intelligence and Machine Learning technologies available to transform existing asset management activities, delivering greater prediction of asset failures which ultimately help to prevent unplanned downtime. On the other hand, we continue to face the same fundamental issues, like work order backlogs and/or limited visibility of operating risks, that were being addressed ten years ago when Asset Performance Management (APM) and predictive analytics solutions first started being implemented across asset intensive industries.

When the dams failed and water flooded the city of Midland, why did the four main pumps all fail at the same time? A failure analysis must be done to find where the problem is. Lack of funds? Pencil whipping? No maintenance? I guarantee that the insurance companies will be looking for this information.

A properly executed maintenance program that can be documented will reduce the insurance costs by at least a million dollars when it comes time to renegotiate premium. Well maybe not this time around.