Ashraf Labib

Review of the main developments in the analytic hierarchy process

In this paper the authors review the developments of the analytic hierarchy process (AHP) since its inception. The focus of this paper is a neutral review on the methodological developments rather than reporting its applications that have appeared since its introduction. In particular, we discuss problem modelling, pair-wise comparisons, judgement scales, derivation methods, consistency indices, incomplete matrix, synthesis of the weights, sensitivity analysis and group decisions. All have been important areas of research in AHP.

Analytic Hierarchy Process and Expert Choice: Benefits and limitations

This article describes the original Analytic Hierarchy Process (AHP) as it is implemented in the software package Expert Choice. We demonstrate its application through a practical example. In particular, we discuss problem modelling, pairwise comparisons, judgement scales, derivation methods, consistency indices, synthesis of the weights and sensitivity analysis. Finally, the limitations of the original AHP along with the new proposed development are explained.

A Fuzzy Quality Function Deployment (FQFD) model for deriving optimum targets

Quality Function Deployment (QFD) is a powerful tool that translates the Voice of the Customer (VoC) into the Engineering Characteristics (ECs), which are those that can be modified in order to meet the desires of the customer. A main objective of QFD is the determination of target values of ECs; however, the conventional QFD aims only empirically at finding these targets, which makes it difficult for the ECs to be optimum. This paper proposes a novel method for determining optimum targets in QFD. Fuzzy numbers are used to represent the imprecise nature of the judgements, and to define more appropriately the relationships between ECs and Customer Attributes (CAs). Constraints such as cost, technical difficulty and market position are considered. An example of a car door is presented to show the application of the method.

A design strategy for reconfigurable manufacturing systems (RMSs) using analytical hierarchical process (AHP): A case study

This paper presents Reconfigurable Manufacturing System (RMS) characteristics through comparison with conventional manufacturing systems in order to address a design strategy towards a RMS. The strategy is considered as a part of a RMS design loop to achieve a reconfigurable strategy over its implementation period. As another part of the design loop, a reconfiguration link between market and manufacturing is presented in order to group products into families (reconfiguring products) and then assign them to the required manufacturing processes over configuration stages. In particular, the Analytical Hierarchical Process (AHP) is employed for structuring the decision making process for the selection of a manufacturing system among feasible alternatives based on the RMS study. Manufacturing responsiveness is considered as the ability of using existing resources to reflect new environmental and technological changes quickly. The AHP model highlights manufacturing responsiveness as a new economic objective along with classical objectives such as low cost and high quality. The forward-backward process is then proposed to direct and control the design strategy under uncertain conditions during its implementation period. The proposed hierarchy is generic in structure and could be applicable to many firms by means of restructuring the criteria. This work is based on a case study in a manufacturing environment. Expert Choice software (Expert Choice 1999) is applied to examine the structure of the proposed model and achieve synthesise/graphical results considering inconsistency ratios. The results are examined by monitoring sensitivity analysis while changing the criteria priorities. Finally, to allocate available resources to the alternative solutions, a (0-1) knapsack formulation algorithm is represented.

A decision analysis model for maintenance policy selection using a CMMS

In this paper, an investigation of the characteristics of computerised maintenance management systems (CMMSs) is carried out to highlight the need for them in industry and identify their current deficiencies. A proposed model provides a decision analysis capability that is often missing in existing CMMSs. The proposed model employs a hybrid of intelligent approaches. This hybrid system is analogous to the Holonic concept. The distinction between these two features is important. The rules function automatically. Practical implications. The main practical implication of this paper is the proposal of an intelligent model that can be linked to CMMSs to add value to data collected in the form of provision of decision support capabilities. A further implication is to identify the need for information to aid maintenance, followed by the provision of reasons for current deficiencies in existing off‐the‐shelf CMMSs.

Grouping and selecting products: the design key of Reconfigurable Manufacturing Systems (RMSs)

A Reconfigurable Manufacturing System (RMS) is a new paradigm that focuses on manufacturing a high variety of products at the same system. Having specified a design strategy for an RMS as the first design step at the tactical level, products must be grouped to identify and allocate corresponding manufacturing facilities. An interface between market and manufacturing called reconfiguration link is presented to specify and arrange products for manufacturing. The reconfiguration link incorporates the tasks of determining the products in the production range, grouping them into families and selecting the appropriate family at each configuration stage. The proposed approach of (re)configuring products before manufacturing facilitates assigning product families to the required manufacturing facilities in terms of (re)configuring manufacturing systems. This paper contributes an overall approach of grouping products into families based on operational similarities, when machines are still not identified. Since the problem of product family selection consists of quantitative and qualitative objectives, the Analytical Hierarchical Process (AHP) is then used while considering both market and manufacturing requirements. The AHP model is verified in an industrial case study through using Expert Choice software. The solutions take advantage of monitoring sensitivity analysis while changing the priorities of manufacturing and/or market criteria. The concept of the proposed model is generic in structure and applicable to many firms. However, the model must be adapted according to the specific nature of the company under study. For instance, product family choices may differ from one company to another because of the available technology and the volume and type of existing products in the production range.

Application of new fuzzy-weighted average (NFWA) method to engineering design evaluation

Engineering design evaluation is characterized by imprecise (vague) importance and satisfaction levels of criteria, which are better treated as fuzzy variables rather than as subjective crisp variables. Nevertheless, operations on fuzzy numbers tend to increase unnecessarily the imprecision when they are combined for some applications, particularly, when a fuzzy-weighted average (FWA) is calculated. This paper proposes a novel method of operating on fuzzy numbers to obtain a fuzzy-weighted average of desirability levels during design evaluation. The method produces overall desirability levels less imprecise and more realistic than those of the conventional FWA. Furthermore, the balance points of these fuzzy numbers seem to be more credible than those of the FWA. An example is presented, which demonstrates the advantages of the method developed.

World‐class maintenance using a computerised maintenance management system

This paper describes industrial research in which the implementation of a computerised maintenace management system (CMMS) was used as an effective tool that supports decision making with the objective of acheiving world‐class manufacturing status. Breakdown trends and performance levels were analysed in a continuous improvement environment. Critical performance measures were then identified and these became the driving force for specific benchmarking metrics and improvement techniques which enabled approaches to eliminate breakdown losses to be formulated. Data collected were analysed using a multiple criteria decision making (MCDM) methodology and the MCDM technique was implemented into the software in order to add value to the data. This gave increased support to decision making and enabled appropriate maintenance strategies to be implemented.

A decision support maintenance management system development and implementation

Competitiveness has forced companies to improve the overall performance of the business. In the area of maintenance, much has been written about strategies, such as total productive maintenance or reliability centred maintenance, in order to increase the reliability and therefore capacity of the industrial plants in their quest for world‐class maintenance. However, if a strategy is to be effective, it must be supported with an invaluable resource, information. In the present work, the role of computerised maintenance management systems (CMMSs) is discussed as a powerful tool necessary for obtaining information from raw data and support the decision‐making process. Furthermore, a CMMS has been designed, developed, customised and implemented for a disc brake pad manufacturing company based in England. In addition, a maintenance maturity grid has been proposed to support the CMMS implementation. The grid shows that the complexity of the CMMS will increase as the maintenance function moves from a reactive to a proactive culture. The implemented CMMS aims to reduce total downtime and frequency of failures of the machines by improving the efficiency and effectiveness of the maintenance force. The computer program simplifies and reduces the time of data capture compared to the currently used paper‐based reporting system. It also provides the maintenance planners with a platform for decision analysis and support often ignored in the commercial CMMSs available in the market.

Gearing Six Sigma into UK manufacturing SMEs: results from a pilot study

Approaches to business improvement have evolved and grown since the early 1900s and today the process focused, statistically driven Six Sigma methodology has been widely used by companies such as GE, Motorola, Honeywell, Bombardier, ABB, Sony, DuPont, American Express, Ford and many other companies in improving the business performance and optimizing the bottom-line benefits. Although Six Sigma business management strategy has been exploited by many world class organizations as mentioned above, there is still less documented evidence of its implementation in small and medium-sized enterprises (SMEs). This paper reports the key findings of a Six Sigma pilot survey in UK manufacturing SMEs. The results of the study are based primarily on descriptive statistics. The results of the study show that many of the SMEs are not aware of Six Sigma and do not have the resources to implement Six Sigma projects. It was also found that Lean Sigma was not generally popular among SMEs. Management involvement and participation, linking Six Sigma to customers and to business strategy are the most critical factors for the successful deployment of Six Sigma in SMEs.