You are probably familiar with life’s golden rule: Do unto others as you would have them do unto you. But have you ever wondered how any given machine, if it could express itself, would feel about this rule? What would it say? This article offers some speculative thoughts from the machine’s point of view, presented as the golden rules for machinery reliability.

Why are organizations leaving money on the table by not investigating failures that cost them money? One would venture to say that all manufacturing companies have failures each year that cut into their profit. The prevailing question is: What do you do when that failure occurs? Do you simply fix the equipment, get back up and running, and return to whatever you were working on at the time? Or, do you stop what you are doing and diligently try to understand why the failure occurred and put measures in place to prevent recurrence?

Traditionally, reliability engineers have been the leaders in introducing new maintenance processes and technologies. With the start of predictive maintenance, many other branches of the organization will become part of the process; at a minimum, there will be strong IT involvement and involvement of the COO or VP of operations. Furthermore, companies might have an IoT strategy unit, a digital unit, or an analytics center, all of which will be interested in the rollout of predictive maintenance.

In some organizations, reliability is not just a word, but a culture that has been built over a period of time. Developing a reliability culture is not solely a top-down approach or dependent on the company’s vision. Sometimes, it is taken as a normal, routine job, while other times, it may get a fast-track status.

Another trite phrase has the answer: The weakest link in a chain is the strongest because it can break it. Preventative and routine maintenance models help alleviate downtime and boost overall production. The most popular method is Total Productive Maintenance (TPM). TPM assigns the responsibility for preventative and routine maintenance to the same people who operate that individual equipment. This puts the people most familiar with the machine in charge of its care.

In the current environment of ever-increasing demands to deliver exceptional results with limited resources, leaders are placing greater emphasis on performance measurement. Performance measurement is defined as the process of analyzing information to determine the progress toward a desired outcome for a given organization.

In today’s competitive funding environment, it’s up to the facility manager to present the case for capital and explain the necessity of addressing deferred maintenance. But where is a facility manager to begin this process when the backlog demanding attention is simply overwhelming?

The Industrial Internet of Things (IIoT) seems like a nebulous concept that encompasses everything from machine learning and robotics to drone delivery systems and intelligent point-of-use vending. There is more information available than ever before, but making sense of all this data can be daunting. This article will help bring clarity to how the IIoT can enhance all aspects of manufacturing.