A methodology for simultaneous optimisation of design parameters for the preventive maintenance and quality policy incorporating Taguchi loss function

Abstract

The performance of a production system depends on the breakdown-free operation of equipment and processes. Maintenance and quality control play an important role in achieving this goal. In addition to deteriorating with time, equipment may experience a quality shift (i.e. process moves to out-of-control state), which is characterised by a higher rejection rate and a higher tendency to fail. This paper develops an integrated model for joint optimisation of preventive maintenance interval and control parameters incorporating the Taguchi loss function. We consider two types of maintenance policies: minimal corrective maintenance that maintains the state of the equipment without affecting the age and imperfect preventive maintenance that upgrades the equipment in between 'as good as new' and 'as bad as old' condition. The proposed model enables the determination of the optimal value of each of the four decision variables, i.e. sample size (n), sample frequency (h), control limit coefficient (k), and preventive maintenance interval (t PM ) that minimises the expected total cost of the integration per unit time. A numerical example is presented to demonstrate the effect of the cost parameters on the joint economic design of preventive maintenance and process quality control policy. The sensitivity of the various parameters is also examined.

Integrated production and maintenance planning for parallel machine system considering cost of rejection

“…where, γ is type II error when process is out of control and can be expressed as in this state due to machine degradation (Montgomery, 2004;Pandey et al, 2012).…”

“…The average number of samples required before the shift is detected is given by: (Pandey et al, 2012)…”

“…IRR can be calculated as follows. If process is being monitored by X control chart with a control limits of ± 3σ (Pandey et al, 2012), then:…”

A Model for Maintenance Planning and Process Quality Control Optimization Based on EWMA and CUSUM Control Charts

“…This integrated maintenance and quality control model uses a PM parametric control chart to provide an optimal time interval and reduce the total costs of the system, as well as to carry out an optimal PM interval and identify an optimal payment order in the production process, which reduces penalty costs because of the schedule delay [27]. Pandey et al [26] also proposed a compact model to optimize PM intervals and a parameterized control chart using a compact Taguchi loss function to reduce the total costs per unit time.…”

Robust parameter design and economical multi-objective optimization on characterizing rubber for shoe soles

“…Some applications of the use of the loss function for optimizing RPD problems for a response can be found in Sharma & Kumar [11] who submitted an application proposal in conjunction with the QFD for provider selection. Pandey et al [12] proposed the use of the loss function for the optimization of a preventive maintenance design and quality policies. Pi & Low [13] proposed the evaluation of suppliers using the loss function as the main weighting.…”