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Purpose: The purpose of this paper is to develop an innovative method of performance appraisal that will be useful for designing a structured training programme. Design/methodology/approach: Employees' performance appraisals are conducted using new approaches, namely data envelopment analysis and an integrated fuzzy model. Interpretive structural modelling is used to design a training programme for employees. Findings: Performance appraisals using data envelopment analysis focus on output enhancement, while an integrated fuzzy model using quality function deployment (QFD) and multi-attribute decision-making focuses on input enhancement. For overall and continuous improvement of employees' knowledge, skills and attributes, this composite model provides an in-depth analysis and also offers a means for designing a structured and effective training programme through interpretive structural modelling. Research limitations/implications: In data envelopment analysis, the number of employees for performance appraisal should be equal to or greater than three times the selected number of input and output factors. In the integrated fuzzy model, the number of main factors should not exceed seven for pairwise comparison. The size of the QFD matrix should not be more than 30. Practical implications: The factors selected for appraisal and the method of appraisal should be known by the employees concerned. Consensus among all those concerned is necessary for effective application and utilization of the model. Social implications: This model provides a means to increase the knowledge, skills and attributes of employees by adopting a structured approach to designing a training programme for employees of various categories. The approaches used are well-established and can be applied in many other fields. Originality/value: In this paper, approaches used for appraisals and designing training programmes are new to this field of study, although they have been successfully proven in many other fields. The results obtained using these methods are useful for helping management to make decisions on training needs, bonuses, incentives and promotions. For the employees, a structured training programme design improves their KSA, quality and standards. (Contains 14 tables and 4 figures.)

Purpose: The aim of this paper is to propose a mapping framework for evaluating supply chain learning potential for the context of small- to medium-sized enterprises (SMEs). Design/methodology/approach: The extracts of recently completed case based research for ten manufacturing SME units and facts reported in the previous research are utilized for the deduction of proposed framework. Initially, 25 learning factors were extracted from the literature which were related to various learning characteristics of SMEs. This helped to develop a mapping framework comprising 55 arguments for evaluating supply chain learning potential/penetration in SME organizations. Findings: An application of the mapping framework is demonstrated for two case organizations. Practical implications: The framework will help SME managers to identify weak areas in their supply chain and adopt learning and knowledge management perspectives to improve upon select dimensions, such as customer responsiveness, flexibility, inventory management and lead time issues through better supply chain planning, coordination and information sharing. Originality/value: The proposed framework integrates the insights reported in three different bodies of knowledge, such as organizational learning, supply chain planning and small and medium scale enterprises, and hence can be seen as a unique supply chain evaluation template for the case of SMEs. (Contains 3 tables and 1 figure.)

In today's changed environment where the economy and industry are driven by customers, business is open to worldwide competition. Manufacturing firms have looked at employee performance improvement as a means to succeed. These findings advocate setting up priorities for employee performance improvement. This requires a continuous improvement training program. In this article, interpretive structural modeling is used to analyze interrelationships among performance appraisal factors to design and plan a training program for employees. (Contains 4 tables and 4 figures.)

Purpose: To explore the potential for adoption of TQM in self-financed technical institutions in the light of new demands and challenges posed by customers/students and society. Design/methodology/approach: The paper presents use of quality function deployment (QFD) which prioritizes technical requirements and correlates them with various customers'/students' requirements for the present Indian context. As an extension to the basic model of QFD: house of quality (HOQ), the scope for futuristic improvements is explored through a four-phased QFD process. Challenges involved in the implementation of TQM are investigated using an approach of force field analysis. Findings: Identifies technical and students' requirements for the modern educational set-up. Provides information about the severity of various technical requirements of competitive education. Recognizes the need for continuous improvement, cultural change and effective use of financial resources to improve the value addition at each level. Develops an understanding of the issues to be addressed at each phase of TQM implementation. Practical implications: It is expected that insights gained will help sensitize the emerging self-financed institutions towards the demands of new age students. Conclusions derived will also provide some opportunities for reflection by students, faculty members and leaders/top management of institutions for continuous development at an individual as well as institutional level. Originality/value: A novelty of work lies in the use of a mix of qualitative and quantitative approaches, which not only evaluates the present system but develops an understanding of future challenges to continuous improvement. (Contains 6 tables and 4 figures.)

Owing to ill-structured, dynamic environments and the presence of multiple decision-makers with conflicting viewpoints, comprehension, analysis and support of the supplier evaluation process becomes more and more difficult. Moreover, with the complexities of issues such as the role of leadership, the influence of group formation, and analysis of disagreements, it cannot be predictable that there will ever exist a solution to cope with all imprecise, multi-criteria/multi-actor situations. A fuzzy association rules-based approach may be suited for the judgement of human subjects. In this paper, we develop an approach based on Fuzzy Association Rule Mining to support the decision makers by enhancing the flexibility in making decisions for evaluating suppliers with both tangibles and intangibles attributes. Also, by checking the fuzzy classification rules, the goal of knowledge acquisition can be achieved in a framework in which assessments could be established without constraints, and consequently checked and compared in several details. The efficacy and intricacy of the proposed model for finding fuzzy association rules from the database for supplier assessment is demonstrated with the help of numerical examples. [ABSTRACT FROM AUTHOR]

This paper presents findings based on an extensive survey of Indian automobile companies. Five companies have been selected for detailed case studies. Their experiences in the manufacturing strategy process are analysed. Although the companies represented a diversity in terms of sales volume, product range and geographic location, they shared several commonalties including use of advanced manufacturing technologies and other improvement activities. Competitive strength was sustained through quality, innovation and delivery. The process of strategy formulation varied among the companies in terms of participants, complexity and degree of formalization, the practice of each company is different. The process of manufacturing strategy formulation seems to be in line with corporate strategy, though the companies followed a traditional top down approach in formulation of manufacturing strategy under the umbrella of corporate strategy. A taxonomy is proposed using cluster analysis where the companies are classified in four strategic manufacturing groups: reactive enterprise, neutral enterprise, active enterprise and proactive enterprises. Competitive priorities, order winners and critical success factors are identified for these companies after rigorous discussions with the managers. Based on strategic manufacturing issues, the manufacturing competence index for the companies has been worked out. A framework for manufacturing strategy is also proposed based on experiences of the case companies. [ABSTRACT FROM AUTHOR]

The CuIn1-xGaxSe2 (CIGS) (x = 0.3) nanocrystalline powder was synthesized by reacting to its constituent elements i.e. Copper, Indium, Gallium, and Selenium in a SPEX mill. The SPEX mill is a high-energy mill where the reaction between constituent elements takes place in solid-state to form a nanocrystalline compound powder. SPEX mill consists of tungsten lined hardened steel vials and tungsten carbide balls are used as grinding media. Three different size grinding media was used with ball to charge ratio of 10 : 1. The optimization of milling time was studied to obtain CIGS nanocrystalline powder using SPEX mill. The phase analysis by X-ray diffraction shows the formation chalcopyrite (tetragonal) structure of CIGS after 4 h of high-energy milling with an average crystallite size of 10-13 nm. Raman spectra peak at 174 cm-1 confirms the formation of the CIGS phase. The compositional analysis by EDAX confirms the formation of the stoichiometric composition of CIGS. This study reveals that it is possible to synthesize CIGS nanocrystalline powder using SPEX mill. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to develop an ontological model of failure knowledge of automobile systems that will enhance the knowledge management of automobile system failures, which will help for design and maintenance of automobiles. Failure knowledge of automobile systems and components gained through maintenance and repair can mitigate future failures, if integrated in the design. This is an outcome of this paper.Design/methodology/approach A failure coding scheme is developed for assimilating various entities of automobile failure knowledge and an ontological model is developed for its systematic structuring and representation. The developed failure code is a combination of alphanumeric and numeric code that incorporates ingredients of the failure knowledge, which will help database management, with reduced data entry time and storage space.Findings The maintenance of automobiles not only brings back the systems into operating conditions but also convey a lot of information regarding the failures. This is a useful input to the designers in development of reliable and maintainable automobile systems. A knowledge base can be created for automobile systems/components failures from their maintenance and service experience.Research limitations/implications Developed ontological model of automobile failure knowledge gained through maintenance experience can be shared across automobile manufacturers and service providers. This would help in design improvements, with ease and efficient undertaking of maintenance activities. This paper proposes the conceptual ontology structure, which is populated with three cases of automobile maintenance.Originality/value This research work is a first attempt to develop an ontological model for automobile failures from their maintenance and service experience. The novelty of the work is in its explicit consideration of all knowledge related to failures and maintenance of automobile systems, with their coding and structuring. [ABSTRACT FROM AUTHOR]

Purpose Integrating sustainability strategies with business processes is the most challenging task for industry professionals due to the lack of a proper understanding of sustainability concepts. At the same time, a lack of proper guidance restricts them from pursuing such activities. As far as the aspects of implementation are concerned, it is very tough to analyse and pick up key points to start with. The purpose of this paper is to utilize a text mining approach to analyse qualitative data and identify the critical issues for implementing sustainability in the manufacturing sector by focussing on turning processes based on the survey responses of researchers and industry professionals.Design/methodology/approach An integrated method employing principal component analysis (PCA) and the k-means clustering algorithm has been applied to extract useful information from a set of various suggestions provided by both the groups surveyed. The textual data has also been visualized using word clouds and, thus, it has been compared with the results of the text mining approach.Findings The results of the study indicate the importance of the role of government organizations and the need for a skilled workforce, which are crucial for enhancing aspects of sustainability in the manufacturing sector, as supported by both researchers and industry professionals. Besides this, researchers have highlighted the need to focus more on environmentally related issues, whereas industry professionals have raised performance-related issues.Practical implications The findings of the study present the important concerns of both the groups towards sustainability initiatives and, thus, will help to enhance the understanding of the underlying possibilities of negotiating jointly to enhance the performance of machining processes.Originality/value The novelty of this paper lies in its identification of important initiatives that are having a direct impact on the sustainable aspects of the machining process, based on the views of researchers and industry professionals. [ABSTRACT FROM AUTHOR]