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The purpose of this paper is to establish a tolerance optimization method based on manufacturing difficulty computation using the genetic algorithm (GA) method. This proposal is among the authors’ perspectives of accomplished previous research work to cooperative optimal tolerance allocation approach for concurrent engineering area.

This study introduces the proposed GA modeling. The objective function of the proposed GA is to minimize total cost constrained by the equation of functional requirements tolerances considering difficulty coefficients. The manufacturing difficulty computation is based on tools for the study and analysis of reliability of the design or the process, as the failure mode, effects and criticality analysis (FMECA) and Ishikawa diagram.

The proposed approach, based on difficulty coefficient computation and GA optimization method [genetic algorithm optimization using difficulty coefficient computation (GADCC)], has been applied to mechanical assembly taken from the literature and compared to previous methods regarding tolerance values and computed total cost. The total cost is the summation of manufacturing cost and quality loss. The proposed approach is economic and efficient that leads to facilitate the manufacturing of difficult dimensions by increasing their tolerances and reducing the rate of defect parts of the assembly.

The originality of this new optimal tolerance allocation method is to make a marriage between GA and manufacturing difficulty. The computation of part dimensions difficulty is based on incorporating FMECA tool and Ishikawa diagram This comparative study highlights the benefits of the proposed GADCC optimization method. The results lead to obtain optimal tolerances that minimize the total cost and respect the functional, quality and manufacturing requirements.

This monograph examines research needs in computer aided production management (CAPM). Recommendations for future research and its organisation are made. The monograph is based on an in‐depth study of current CAPM practice in a varied sample of 33 companies. The study conclusions confirm many existing beliefs. Many companies are paying inadequate attention to the necessary prerequisites for successful CAPM implementation. The prerequisites change as the extent of CAPM system integration increases. Organisational rather than implementation issues dominate as integration increases. The proposed research would bring together existing knowledge of best CAPM practice to form methodologies for the audit, design and implementation of CAPM systems. The aim is to reduce the time‐span of the learning curve required for successful CAPM integration. The methodologies need to be specific to particular industrial sectors.

Suggests that, in many cases, where formerly excellent manufacturing companies have suffered a decline in their fortunes, they failed because they did not change with their customers; their operations were too remote. Considers how this might be avoided by applying a service quality model to manufacturing. Examines the differences between service and manufacturing operations and highlights the difficulties which manufacturing companies have in being close to their customers. Provides definitions of quality for products and services before presenting the model. Describes the features of the model – taking a total view, achieving a balance between expectations and delivery, system design and response to change‐as they apply both to service and manufacturing. Highlights the need to exceed expectations to maintain a competitive edge. Argues that, whilst this is achieved through committed staff in service industries, this same commitment can, with appropriate communication, be achieved in manufacturing companies.

The purpose of this paper is to propose a methodology to estimate manufacturing complexity for both machining and layered manufacturing. The goal is to take into account manufacturing constraints at design stage in order to realize tools (dies and molds) by a combination of a subtractive process (high‐speed machining) and an additive process (selective laser sintering).

Manufacturability indexes are defined and calculated from the tool computer‐aided design (CAD) model, according to geometric, material and specification information. The indexes are divided into two categories: global and local. For local indexes, a decomposition of the tool CAD model is used, based on an octree decomposition algorithm and a map of manufacturing complexity is obtained.

The manufacturability indexes values provide a well‐detailed view of which areas of the tool may advantageously be machined or manufactured by an additive process.

Nowadays, layered manufacturing processes are coming to maturity, but there is still no way to compare these new processes with traditional ones (like machining) at the early design stage. In this paper, a new methodology is proposed to combine additive and subtractive processes, for tooling design and manufacturing. A manufacturability analysis is based on an octree decomposition, with calculation of manufacturing complexity indexes from the tool CAD model.

This research paper aims to: explore areas of weakness in six sigma implementations that may require enhancements in the methodology; to investigate implementation differences between manufacturing and services; and to investigate critical success factors.

Exploratory empirical evidence is presented from nine case study companies in Thailand, including manufacturers, sales and service companies and a national airline.

Key findings include: six sigma is more appropriate for high risk, complicated, large‐scale and cross functional projects; the six sigma methodology could be enhanced to ensure that projects are aligned to company goals; the evidence questions standard text book advice that a “Black Belt” (BB) should have a full time role, as a part‐time BB role can be more realistic particularly in a small company and the training materials available need to be improved to be more appropriate for service operations.

The main research limitation is in the number of companies studied and the restriction to companies located in Thailand. In addition, the research is exploratory and future research is needed to look at the issues raised in depth.

All of the findings have practical implications. For example, the conclusion on the nature of the BB role is seen as a key issue for successful use of six sigma in small businesses.

Six sigma has been widely used in industry, but there has been limited rigorous academic research. This paper seeks to identify a series of issues worthy of further attention from the academic community using a rigorous research approach.

In the case of mass customization, product variety leads to exponentially increased variation in the production system. Providing flexible manufacturing solution for customized product rapidly is the key measure to achieve the goal of cost and delivery time. The purpose of this paper is to address these issues.

Following introduction, the paper describes flexible manufacturing and numerical control (NC) machining techniques in mass customization. The kernel idea is that NC program for mass customization product should be generated from parametric manufacturing information template, so as to achieve NC program variant design in accord with product variant design. The elements of NC programming system discussed in this paper address the definition of machining feature, the development of NC subprogram, template construct, and the architecture of NC programming system for mass customization product.

Machining feature, NC subprogram, and template are made to help manufacturing system to deal with the increased variation requirements resulting from product variety. The effects can be verified by the case study.

This paper provides a practical NC programming system for mass customization product and makes detailed technical solution to manufacturing system developer and its applications.

Over the last two decades, Japanese products have challenged Western ones, not only in terms of cost but also on quality, reliability and delivery. This has meant that meeting customer needs on time has now entered the competitive equation. Hence, in the 1990s, time to market (TTM) has become a focal point in achieving competitive advantage in the marketplace. Presents an overview of TTM and of how to do it. Considers the costs and benefits of TTM, and uses two case studies to compare and contrast the effect of adopting TTM and ignoring it. Looks at the key factors of: tools and techniques; technology; team management and logistics, with practical examples of the main points in achieving TTM successfully.

The six sigma methodology has been successfully implemented in many organizations leading to tremendous quality improvements in products manufactured and services delivered. However, academic institutions have lagged other organizations in implementing six sigma. The purpose of this paper is to examine the challenges of implementing the methodology in academia and proposes a framework that serves as a guide for implementing six sigma in academic institutions.

Several unique aspects that differentiate an academic environment from a manufacturing setting for six sigma are identified. A three‐tiered framework to organize the six sigma improvement methodology and related academic performance indicators into a hierarchy fitting academic institution governance levels is proposed. Examples of strategic objectives and performance indicators by levels of implementation for the DMAIC process are also provided.

The findings suggest that the unique structure of an academic institution make it an interesting candidate for implementing six sigma. The three‐tiered framework for six sigma can be used by administrators, faculty, staff and students as an implementation guide.

The paper shows that significant differences between the environments make implementation in many areas within an academic institution challenging. However, there are limitations to the application of six sigma in an academic organization. The six sigma methodology has been more thoroughly developed and refined in manufacturing environments than in service systems such as in a university.

This paper helps to stimulate thinking about the application of a proven quality management methodology to academic settings where structured formal improvement programs such as six sigma are not commonly found.

The value of this paper is to provide a three‐tiered hierarchical structure for applying six sigma in academic organizations.

The purpose of this paper is to present a novel Kriging meta-model assisted method for multi-objective optimal tolerance design of the mechanical assemblies based on the operating conditions under both systematic and random uncertainties.

In the proposed method, the performance, the quality loss and the manufacturing cost issues are formulated as the main criteria in terms of systematic and random uncertainties. To investigate the mechanical assembly under the operating conditions, the behavior of the assembly can be simulated based on the finite element analysis (FEA). The objective functions in terms of uncertainties at the operating conditions can be modeled through the Kriging-based metamodeling based on the obtained results from the FEA simulations. Then, the optimal tolerance allocation procedure is formulated as a multi-objective optimization framework. For solving the multi conflicting objectives optimization problem, the multi-objective particle swarm optimization method is used. Then, a Shannon’s entropy-based TOPSIS is used for selection of the best tolerances from the optimal Pareto solutions.

The proposed method can be used for optimal tolerance design of mechanical assemblies in the operating conditions with including both random and systematic uncertainties. To reach an accurate model of the design function at the operating conditions, the Kriging meta-modeling is used. The efficiency of the proposed method by considering a case study is illustrated and the method is verified by comparison to a conventional tolerance allocation method. The obtained results show that using the proposed method can lead to the product with a more robust efficiency in the performance and a higher quality in comparing to the conventional results.

The proposed method is limited to the dimensional tolerances of components with the normal distribution.

The proposed method is practically easy to be automated for computer-aided tolerance design in industrial applications.

In conventional approaches, regardless of systematic and random uncertainties due to operating conditions, tolerances are allocated based on the assembly conditions. As uncertainties can significantly affect the system’s performance at operating conditions, tolerance allocation without including these effects may be inefficient. This paper aims to fill this gap in the literature by considering both systematic and random uncertainties for multi-objective optimal tolerance design of mechanical assemblies under operating conditions.

In recent years, companies have been using brand extensions as a strategy for launching new products. The reason why this strategy has been popular is the fact that it decreases the risk of failure of new products, because consumers initially are more willing to accept products marketed under known brands. Nevertheless, this strategy is not free from risks, since it is not convenient for all the brands, and moreover it may have negative effects on the image of the extended brand. Therefore, the main objective of this study is to analyse the influence that brand extensions have on brand image. For this analysis, an experiment is performed that examines the most important variables to consider in using the brand extension strategy. After analysing the information obtained, reaches the conclusion that brand extension strategies may influence the brand image after the extension and that variables such as the brand image prior to the extension, the perceived quality of the extension and the fit between the parent brand and the new product also affect the image.