M.A. Rahim and Khaled S. Al‐Sultan
Recently, there has been a lot of interest in the economics of quality control. Many researchers have considered the problem of determining the optimal target mean for a process…
Abstract
Recently, there has been a lot of interest in the economics of quality control. Many researchers have considered the problem of determining the optimal target mean for a process, but almost all of them have assumed that the process variance is fixed and known in advance. The problem of simultaneously determining the optimal target mean and target variance for a process is considered. This might result in a reduction in variability and in the total cost of the production process. A reduction in variability upholds the modern concept of Taguchi’s loss function, which states that any deviation from the target value incurs economic loss, even when the quality characteristic lies within the specification limits. Taguchi’s loss function is incorporated to extend this study further to jointly determine the optimal target mean and variance.
Details
Keywords
S.O. Duffuaa and K.S. Al‐Sultan
Addresses the problem of maintenance planning and scheduling and reviews pertinent literature. Discusses the characteristics and the complexity of the problem. Advocates…
Abstract
Addresses the problem of maintenance planning and scheduling and reviews pertinent literature. Discusses the characteristics and the complexity of the problem. Advocates mathematical programming approaches for addressing the maintenance scheduling problem. Gives examples to demonstrate the utility of these approaches. Proposes expansion of the state‐of‐the‐art maintenance management information system to utilize the mathematical programming approaches and to have better control over the maintenance scheduling problem.
Details
Keywords
The purpose of this paper is to illustrate an uncertain programming model for scheduling of preventive maintenance (PM) actions. The PM scheduling, in which PM actions are…
Abstract
Purpose
The purpose of this paper is to illustrate an uncertain programming model for scheduling of preventive maintenance (PM) actions. The PM scheduling, in which PM actions are performed under fixed intervals, is solved by grey systems theory.
Design/methodology/approach
The paper applied the grey evaluation method based on triangular whitenization weight functions which includes two classes: endpoint evaluation method and center-point evaluation method.
Findings
Two methods give the same results based on endpoint and center-point triangular whitenization weight functions. For validation, the results were compared by Cassady’s method.
Originality/value
The scheduling of PM is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. It is helpful to reduce the outage loss on frequent repair/replacement parts and avoid lack of maintenance of the equipment by controlling the equipment maintenance frequency.
Details
Keywords
S.O. Duffuaa, M. Ben‐Daya, K.S. Al‐Sultan and A.A. Andijani
Maintenance is a complex process that is triggered by equipment failure or planned repair. This process requires planning, scheduling, control and the deployment of maintenance…
Abstract
Maintenance is a complex process that is triggered by equipment failure or planned repair. This process requires planning, scheduling, control and the deployment of maintenance resources to perform necessary maintenance activities. In this paper a generic conceptual model for maintenance systems has been developed. The conceptual model consists of seven modules. The first one is the input module in which the characteristic of the maintenance system is specified. The second module is concerned with modeling the maintenance load. The third module is the planning and scheduling. This module is the most critical, since it controls the maintenance process. The fourth module is the material and spare parts supply, followed by the equipment availability module. The sixth module is the quality control module and the performance measures are the seventh module. The specification of such a conceptual model lays the ground for developing a realistic simulation model.
Details
Keywords
S.A. Oke and O.E. Charles‐Owaba
The purpose of this paper is to work on an analytical approach to test sensitivity of a maintenance‐scheduling model. Any model without sensitivity analysis is a “paper work”…
Abstract
Purpose
The purpose of this paper is to work on an analytical approach to test sensitivity of a maintenance‐scheduling model. Any model without sensitivity analysis is a “paper work” without advancing for wider applications. Thus, the simulation of simultaneous scheduling of maintenance and operation in a resource‐constrained environment is very important in quality problem and especially in maintenance.
Design/methodology/approach
The paper uses an existing model and presents a sensitivity analysis by utilising an optimal initial starting transportation tableau. This is used as input into the Gantt charting model employed in the traditional production scheduling system. The degree of responsiveness of the model parameters is tested.
Findings
The paper concludes that some of these parameters and variables are sensitive to changes in values while others are not.
Research limitations/implications
The maintenance engineering community is exposed to various optimal models in the resource‐constraint‐based operational and maintenance arena. However, the models do lack the sensitivity analysis where the present authors have worked. The work seems significant since the parameters have the boundary values so the user knows where he can apply the model after considering the constraints therein.
Originality/value
The underlying quest for testing the sensitivity of the model parameters of a maintenance scheduling model in a multi‐variable operation and maintenance environment with resource constraints is a novel approach. An optimal solution has to be tested for robustness, considering the complexity of the variables and criteria. The objective to test the model parameters is a rather new approach in maintenance engineering discipline. The work hopefully opens a wide gate of research opportunity for members of the maintenance scheduling community.
Details
Keywords
Abubaker Shagluf, Simon Parkinson, Andrew Peter Longstaff and Simon Fletcher
The purpose of this paper is to produce a decision support aid for machine tool owners to utilise while deciding upon a maintenance strategy. Furthermore, the decision support…
Abstract
Purpose
The purpose of this paper is to produce a decision support aid for machine tool owners to utilise while deciding upon a maintenance strategy. Furthermore, the decision support tool is adaptive and capable of suggesting different strategies by monitoring for any change in machine tool manufacturing accuracy.
Design/methodology/approach
A maintenance cost estimation model is utilised within the research and development of this decision support system (DSS). An empirical-based methodology is pursued and validated through case study analysis.
Findings
A case study is provided where a schedule of preventative maintenance actions is produced to reduce the need for the future occurrences of reactive maintenance actions based on historical machine tool accuracy information. In the case study, a 28 per cent reduction in predicted accuracy-related expenditure is presented, equating to a saving of £14k per machine over a five year period.
Research limitations/implications
The emphasis on improving machine tool accuracy and reducing production costs is increasing. The presented research is pioneering in the development of a software-based tool to help reduce the requirement on domain-specific expert knowledge.
Originality/value
The paper presents an adaptive DSS to assist with maintenance strategy selection. This is the first of its kind and is able to suggest a preventative strategy for those undertaking only reactive maintenance. This is of value for both manufacturers and researchers alike. Manufacturers will benefit from reducing maintenance costs, and researchers will benefit from the development and application of a novel decision support technique.
Details
Keywords
Khaled S. Al‐Sultan and Salih O. Duffuaa
Maintenance control plays a key role in achieving the statedobjective of effectiveness and efficiency of the maintenance system. Ina recent paper, Gits proposed a reference…
Abstract
Maintenance control plays a key role in achieving the stated objective of effectiveness and efficiency of the maintenance system. In a recent paper, Gits proposed a reference framework that guides in the design and structuring of maintenance control. The framework is conceptual in nature and its use in practice is limited. Poses Gits’ framework as a set of mathematical programming models. Extends some of Gits’ procedure for maintenance control, then outlines the required expansion in the maintenance management information system (MMIS) in order to provide the needed data to execute the models. The models provide operational plans and schedules ready for implementation.
Details
Keywords
The purpose of this paper is to integrate the decisions regarding optimal process mean and the parameters of a sampling plan.
Abstract
Purpose
The purpose of this paper is to integrate the decisions regarding optimal process mean and the parameters of a sampling plan.
Design/methodology/approach
A model is developed to determine these parameters. The model maximizes producer expected profit, while protecting the consumer through a constraint on the probability of accepting lots with low incoming quality. The model is presented for two cases. The first one is for non‐destructive testing and the other for destructive testing. An example is presented to demonstrate that the utility of the model and sensitivity analysis on key parameters of the model has been conducted.
Findings
The findings indicated that the optimal parameters for the process and the sampling plan are significantly different from when determined separately. The sensitivity analysis showed that the process parameters are very sensitive to changes in the process variance, moderately sensitive to the limit on incoming quality, and insensitive to the consumer risk and inspection cost.
Practical implications
The models developed offer an alternative approach for quality managers to address setting process targets, taking into consideration a sampling plan.
Originality/value
The originality of the paper is in the integration of two elements of quality that are usually treated separately in the literature.
Details
Keywords
This paper describes an actual aircraft maintenance labor scheduling study. The study’s objective is to determine the optimum maintenance workforce schedule to satisfy growing…
Abstract
This paper describes an actual aircraft maintenance labor scheduling study. The study’s objective is to determine the optimum maintenance workforce schedule to satisfy growing labor requirements with minimum cost. The main recommendation of the study is to switch from a five‐day to a seven‐day workweek for aircraft maintenance workers. A new integer programming formulation, used to obtain an optimum seven‐day work schedule with no increase in workforce size, is presented. In comparison to the existing five‐day schedule, switching to a seven‐day workweek is expected to produce savings of about 13 per cent, or $100,000 annually.
Details
Keywords
Paul L. Goethals and Byung Rae Cho
The selection of the optimal process target for a manufacturing process is critically important as it directly affects the defect rate, rejection and rework costs, and the loss to…
Abstract
Purpose
The selection of the optimal process target for a manufacturing process is critically important as it directly affects the defect rate, rejection and rework costs, and the loss to customers. A recent review of process target literature suggests that future work should incorporate models using multiple quality characteristics. Thus, the purpose of this paper is to create a more flexible and realistic approach to solving the multi‐response process target problem.
Design/methodology/approach
A design of experiments methodology is proposed to provide estimates of process parameters and a nonlinear constrained optimization scheme is employed to identify optimal settings.
Findings
The approximation of cost savings undoubtedly has a higher degree of accuracy than in the case where the engineer assumes values for the process parameters. Furthermore, greater flexibility is obtained in finding solutions that support both the manufacturer and the customer.
Research limitations/implications
This methodology relies on controlled experimentation and the replication of observations made on multiple nominal‐the‐best quality characteristics. Future research may include examining the effects of using smaller‐the‐better or larger‐the‐better type characteristics.
Originality/value
Unlike traditional attempts at solving the process target problem where the process mean, variance, and covariance between characteristics are assumed known in advance, this paper uses an approach that removes these assumptions, thereby providing a more practical depiction of the overall system. Furthermore, this methodology broadens the scope of process target problem research by seeking the simultaneous optimization of process parameters and considering a loss in quality attributed to deviation from a target value.