Abstract
Developments in sensor equipment and the Internet of Things increasingly allow production facilities to be monitored and controlled remotely and in real-time. Organizations can exploit these opportunities to reduce costs and improve reliability by employing condition-based maintenance (CBM) policies. Another recently proposed option is to adopt condition-based production (CBP) policies that control the deterioration of equipment by dynamically adapting the production rate. This study compares their performance and introduces a fully dynamic condition-based maintenance and production (CBMP) policy that integrates both policies. Numerical results show that their cost-effectiveness strongly depends on system characteristics such as the planning time for maintenance, the cost of corrective maintenance, and the rate and volatility of the deterioration process. Integrating condition-based production decisions into a condition-based maintenance policy substantially reduces the failure risk, while fewer maintenance actions are performed. Interestingly, in some situations, the combination of condition-dependent production and maintenance even yields higher cost savings than the sum of their separate cost savings. Moreover, particularly condition-based production is able to cope with incorrect specifications of the deterioration process. Overall, there is much to be gained by making the production rate condition dependent, also, and sometimes even more so, if maintenance is already condition-based.
Highlights
Maintenance activities are a major cost driver for modern production facilities
We address whether a flexible production planning replaces the need for a flexible maintenance planning
The major insights are that (1) all strategies realize a significant cost saving for all values of γ, (2) for concave pd-relations condition-based maintenance (CBM) is preferred while CBP is better for ‘more convex’ pd-relations, (3) CBM and CBP complement each other for all values for γ, and (4) condition-based production decisions improve the CBM policy even if μmin is high compared to μmax
Summary
Maintenance activities are a major cost driver for modern production facilities. For instance, manufacturing firms typically face maintenance costs ranging between 15-40% of their total expenses (Wireman, 2014), and for power plants and offshore wind farms maintenance costs constitute up to 30% of the total costs (Blanco, 2009; Graber, 2004). These developments enable operators to monitor and control production facilities remotely and in real time In light of these developments, many studies aim to reduce maintenance costs by implementing flexible maintenance policies that schedule maintenance based on condition information. That reduces operational costs but does not require a flexible maintenance schedule, is to control the deterioration of equipment by dynamically adapting the production rate based on condition information (Uit het Broek et al, 2019). This approach exploits the fact that machines typically deteriorate faster at higher production rates.
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