How to achieve PdM success: Be like Mike

Michael Macsisak is a predictive maintenance technician to the food processing plant Nestle Purina pet in Allentown, Pennsylvania, which helps produce Friskies, powerful brands Alpo dog and pet foods. Recently, the maintenance team Allentown plant launched a multi-year project to improve the reliability of assets maintenance throughout the plant by taking focused on reliability prediction approaches and technologies. Macsisak, who has 30 years of experience in mechanics and heavy equipment mechanic, production line, crane mechanic, millwright and welder, was part of the team that was done to make this change. Now is a technician level II ultrasound technician IR Level I Machinery Lubrication Technician and Technical Experts laser alignment level II, and today is training as a data analyst Level I Vibration. Plant Services Macsisak spoke on the challenges associated with change, and the impact it has had predictive maintenance reliability of both assets and team player and trust.

PS: Can you describe the original focus of his team for maintenance before the start reliability initiatives?

MM: There are several years the original function of the maintenance team was reactive - a recipe for failure and only fighting fires. The most frequent questions always were, "How long until we're back" and "we can do for the weekend without finishing the repair?"

In addition, success was defined as any time before the broken piece of equipment installation closed. Repair rate was the norm for our mechanics. quick repair deserved a gold star.

PS: After the reliability of initiatives have been implemented, what are some of the major changes in the work that took time to get used to it?

MM: We planted new routes predictive maintenance as required by the history of machine breakdowns. Within months, we started getting positive results with PDM. Initially, we had 20 pieces of equipment with predictive maintenance routes, and all have trended with excellent results, including $ 1.4 million in production due to planning adequately predict repairs and planning team.

The new standard for gold stars predicted failures, and planning required around the production needs repairs. Control now when fix things rather than when we have a breakdown. The mechanics are trying to check and verify all machines constantly instead of waiting for failure to occur with a turnkey. dedicated teams now record and analyze trends routes. We have machines instead of machines we have.

PS: What advice would you give experienced workers / veterans who try to make the same change you and your team have done?

MM: Change is good. It can be difficult for older dogs to learn new tricks, but from my experience, the change was the best thing that can happen to me.

PDM developed in our establishment, the spirit of the new equipment installations has also changed. Before predictive maintenance, equipment and important work would happen just to get it up and running, resulting in additional costs and headaches. Maintenance programs focused on reliability and PDM grew not only computer functionality and the ability of mechanics, but the mentality of the entire installation.

The key to making the transition from a mechanic to predictive maintenance technician is in the mood. If you believe in failure prediction and understanding of the root cause, PDM is the place to start. PdM focuses on roads and routine: roads should be monitored regularly and continuously to ensure a thorough understanding of the equipment is in bad trend. Determine routes based on a daily, weekly or monthly and complete the roads when needed.

Among oil analysis, vibration, infrared and ultrasound, you can follow each of the machines in their facilities with excellent results. Many other tools are available free of charge and training minor, including Centerlining, 5S and ODB (Break Down Analysis). All these tools are fantastic ways to get to the root cause of his team; However, PDM is the only way to predict the trend and a piece of equipment before it actually breaks.

Always have more wins than losses, with strong predictive equipment maintenance. do not buy for the price we buy for reliability. You can never put a price on reliability.