Those involved in maintenance operations are enjoying the benefits of information and communication technology in the planning and management of maintenance activities, resource management and planned production. In the digital space, the computer-based operating systems, commonly referred to as computerised maintenance management systems (CMMSs), enable quick and effective communication between stakeholders, facilitate improved planning, easy access to historical data, reporting and performance improvements of the maintenance function. However, success in the use of CMMSs depends on the human capacity of the users of the system. In practice, many organisations use the CMMS tool for planning, operations management and reporting, without the aid of detailed analysis of operational information in the CMMS database. They fail to harness all the possible benefits. Three case studies were used to illustrate the situation. Two of them refer to academic institutions and the third is a manufacturing company. In the academic institutions, the CMMS was used for maintenance planning, management and periodic reporting. The manufacturing company included analysis of the information in the operational database, which culminated in identifying the level of the reliability of machines in the production network through benchmarking. The conclusion is that the quality of the human capacity enables organisations to harness and make maximum use of the potentials inherent in typical CMMS software.
The objective of the manufacturing industry is to produce quality and quantity of goods to satisfy existing customer base, expand market sphare, remain competitive and profitable. However, achieving these ideals depend largely on the reliability of the machines in the production line. Therefore, it is necessary to explore the impact of machine reliability on production and profiability in a manufacturing industry by analysing and interpreting the operational information in the computerised maintenance management system (CMMS) database.This research adopted the principle of action research, involving a two-year longitudinal analysis of the operational information in the database of the machines in the production line of Adcock Ingram Critical Care (AICC) and benchmarking the same with that of Adcock Ingram Health Care (AIHC), a similar pharmaceutical industry. It focused on how AIHC used the factors of total breakdowns, total down time, mean time between failure (MTBF) and the mean time to repair (MTTR) to improve on the reliability of machines in their production network. The analysis was complemented with interviews of participants from inter-related units of the same industry. The findings revealed that in all the areas of measurement in 2017, the machines in the production line of AICC performed below the benchmark of AIHC. However, in 2018, there were appreciable improvements, due to the practice of preventive maintenance. Therefore, the introduction of appropriate CMMS in maintenance operations, including the detailed analysis of operational information and benchmarking, provides a useful learning curve to improve on the reliability of machines in the production line of manufacturing industries.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.