As Industry 4.0 continues to mature across manufacturing enterprises globally, many assume that new technologies will replace old methodologies to spur continued improvements in efficiency and production. And while that may be the case for some applications, it is also true that these new technologies can be complementary to existing practices.
One such methodology that aligns especially well with the value offerings of Industrial IoT applications is that of Total Productive Maintenance (TPM). Built on the 5S foundation popularized by lean methodology, TPM is a maintenance model that helps alleviate downtime and improve production. Using this model, downtime for maintenance is included in manufacturing as part of manufacturing scheduling. Operators and technicians, those most familiar with the equipment, are given responsibility for certain aspects of preventive and regular maintenance as part of their responsibilities.
The goal of TPM is to improve productivity, efficiency, and safety while building a culture that includes basic maintenance into standard operating procedures for line staff. This includes 8 pillars of activity:
So how does TPM align with the value offerings of the Industrial IoT? Rather than being a methodology at odds with a new technology, it is easy to see that programs such as TPM are almost tailor made for IIoT. A strong and comprehensive Industrial IoT platform will offer several things:
Shop floor visualization is important at multiple levels of the organization, from technicians to plant managers.
At MachineMetrics, the goal of the data is to provide you with real-time visualization and analysis that fully aligns with all three. And data is what makes MachineMetrics so good at what we do. By driving value through the use of analytics, MachineMetrics helps customers improve their OEE and manufacturing efficiency as well as identifying bottlenecks in production. This drives value through the use of analytics throughout the operation.
TPM is different from traditional preventive maintenance. In traditional maintenance programs, a time-oriented list is utilized based on OEM recommendations. This method of maintenance does not factor in production materials that put aggressive or mild strain on equipment, meaning that equipment either malfunctions sooner than expected or much longer than expected. One adds cost in the form of breakdowns and the other adds cost in the form of replacing parts that are still in optimal working order. MachineMetrics helps customers with advanced machine learning, deep analytics, and intuitive and customized dashboards that allow operators, technicians, and managers to act in real-time at a level not previously possible.
Traditional maintenance is also not predictive. And being matrix-based rather than analytics-based, traditional maintenance relies on pre-set time to perform maintenance. It does not have the ability afforded IIoT technology to schedule the maintenance in conjunction with changeovers or other scheduled downtime to reduce overall downtime. We’ve seen this time and time again at MachineMetrics. Our software brings the benefits of Industrial IoT to the production floor, allowing customers to develop dynamic, data driven maintenance programs that save time and money.
Intuitively, the effectiveness of TPM is made possible by the value offerings of the Industrial IoT. By providing data from vibration sensors, temperature sensors, and wear sensors, IIoT allows for accurate and actionable capture of data that makes full realization of TPM possible. In doing so, the potential of the “Hidden Factory” is unlocked and digital lean can be realized through the use of IIoT technology by building on lean principles.
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