Abstract
Modern production systems must guarantee high performance. Increasingly challenging international competition, budget reductions for the health sector and constant technological evolution are just three of the many aspects that drive pharmaceutical companies to continuously improve the productivity of their lines.The scientific literature has for many years been proposing calculation models for estimating the productivity of a machine. One of the most famous, and still used, is overall equipment effectiveness (OEE). This allows the calculation the valuable output considering the six ‘big losses’. The limitations of this approach are noticeable when considering a production line instead of a single machine. Numerous researchers have proposed alternative methods or changes in OEE, to be able to cover the widest spectrum of possible cases.In this study, we wanted to evaluate how such theoretical models related to OEE are actually able to represent the world of tight production flows or whether, in these cases, a more complex type of simulation should be preferred. To do this, we carried out a case study of a production line in the pharmaceutical industry, and the results showed that the simulation approach gives better results because of the peculiarities not considered by the theoretical models.
Highlights
In the industrial sector it is increasingly common to employ methods and tools to measure production performance
Starting from the log data of the production line, we prepared the necessary information for the calculation of, and and, in particular, the load times, failures, setup times, and the time lost due to non-measurable stops and to loss of quality
The application of the models presented previously has shown how the simulation approach is more suitable for representing the packaging line considered in this study
Summary
In the industrial sector it is increasingly common to employ methods and tools to measure production performance. In the literature there are many papers that deal with the measurement of system performance [2] [3] [4] [5]. In the production field in particular this shifted the focus of performance from the financial to different aspects, widely spread until at least the end of the 1980s [6]. Since productivity is so crucial in production management, many methods have been developed recently in order to improve the performance of a line in various industrial fields [7]
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