Machinery classification and prioritization: Empirical models and AHP based approach for effective preventive maintenance

Empirical models play an important role in the classification of machinery for scheduling preventive maintenance (PM) activities for machinery in manufacturing firms (MFs). First, this manuscript discusses the development of empirical models for classifying machines in an MF and the structure of each empirical model. Then, it presents the classification of machinery using the developed empirical models in two different manufacturing areas. It then goes on to demonstrate the development of a common model for the two different manufacturing areas in the case study MF. It is a challenge to allocate the available resources, when the classified groups contain a large amount of machinery. Hence, machines have been grouped into families or types based on their similarities, and an analytic hierarchy process (AHP) has been employed to further prioritize each type of machinery. A generic hierarchical model has been developed to prioritize machinery in the case study MF. Then, the use of AHP has been demonstrated using a tailor-made hierarchical model based on a selected type of machinery, focusing on prioritizing the necessary PM activities.