Preventive maintenance rules of thumb and best practices have been used in fleet shops for decades. Increasingly modern, yet still basic solutions utilize data to focus those general guidelines and turn them into maintenance plans geared for basic equipment monitoring.
Fast forward to the work of today’s proactive and future-focused fleets. Advancing beyond basics, predictive maintenance systems not only monitor, but analyze data from repair orders, fluid analysis, consumption rates, truck telematics, fault codes and other sources to provide predictive information on near-term failures or fault conditions to maintenance directors and their technicians.
Capitalizing on volumes of data, predictive maintenance algorithms keep tractors and trailers rolling smoothly between regularly scheduled shop visits and avoid pending part and system failures. Fewer breakdowns mean higher vehicle uptime, lower maintenance costs and more predictable scheduling and inventories.
Greg Peck joined TMW in 1998 and has since served TMW customers through key areas including customer support, quality, implementation, analysis, consulting services and others. Prior to joining TMW, Greg managed maintenance needs for a variety of LTL, Truckload and Refrigerated carriers. In his current role Greg is responsible for strategic level product planning of Asset Maintenance tools from TMW.
Russ McKusick is the Warranty Manager at wholesale distributor Bozzuto’s Inc. McKusick’s work spans nearly forty years in maintenance roles, including an ongoing emphasis in warranty, service and and parts management. Through these roles, McKusick has been responsible for warranty processing and claim payments for manufacturers, leasing companies and most recently a private fleet. He has also been responsible for the productivity and efficiency of of multiple service departments in Connecticut. While his role expands beyond fluids and parts, McKusick is responsible for Bozzuto’s focus on fluid monitoring within their shops. This work has lead to prevention that is focused on understanding fluid usage and developing plans designed to decrease equipment failures based.
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