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The purpose of this paper is to propose a new software tool to support design for quality (DfQ) in the electronics manufacturing sector where quality and reliability are critical.

An integrated modelling framework that enables complete and realistic representations of manufacturing systems is proposed. A software tool, developed based on this framework, offers two modules to support DfQ: simulation and root cause analysis. This paper focuses on the latter.

Integrated models enable tracing back effects to their root causes. Software tools based on these, kind of models can provide support in finding and eliminating the cause of a particular effect. This capability can be used to perform DfQ in an effective and accurate way.

The approach proposed strongly depends on the quality models within the integrated modelling framework. The models currently available are little and simplified. Future work includes the enrichment of the software by developing and more quality models.

The adoption of the proposed approach in an industrial context requires formalised information to fulfil the data required by the integrated modelling framework.

The main contribution of the paper is the integrated modelling framework definition and its implementation in the form of a software tool. The adoption of this tool in printed circuit assembly companies can support the solution of real quality problems and consequently, help to optimise manufacturing systems in the domain.

The purpose of this paper is to provide sector-specific empirical evidence on the comparative evaluation of total productive maintenance (TPM) and total quality management (TQM) approaches, implemented exclusively and collectively on improving manufacturing business performance.

This paper develops a multi-sector analysis framework to comparatively assess the synergistic and standalone effect of TPM and TQM improvement approaches. A total of 231 manufacturing organizations from food and beverages, textiles and electrical and electronics sectors have been extensively surveyed. These firms were further clustered into TPM focus, TQM focus and integrated TPM×TQM on the basis of their primary manufacturing strategy. Comparative assessment of these three manufacturing approaches has been evaluated using t-test statistics.

This paper highlights that adoption of integrated TPM×TQM approach is beneficial for food and beverages and electrical and electronics sectors. However, this supposition is rejected for firms operating in the textile sector.

The findings of this research are still exploratory. Future research using countrywide and cross-country approach can be undertaken to statistically generalize the findings of the present research. In-depth case studies are needed to further validate the findings of the study empirically.

The result of this study help managers and practitioners to make manufacturing strategic decision based on the nature of their operating business sector regarding adoption of TPM and TQM practices, which will further revive their firm’s competitiveness.

Every operating sector embraces a diversity of manufacturing activities based upon their competing priorities. This paper makes an attempt to present a multi-sectoral evaluation of joint implementation and effect of manufacturing programs.

In implementing Six Sigma and/or Lean Six Sigma, a practitioner often faces a dilemma of how to select the subset of root causes from a superset of all possible potential causes, popularly known as root cause analysis (RCA). Generally one resorts to the cause and effect diagram for this purpose. However, the practice adopted for identification of root causes is in many situations quite arbitrary and lacks a systematic, structured approach based on the rigorous data driven statistical analysis. This paper aims at developing a methodology for validation of potential causes to root causes to aid practitioners.

Discussion has been made on various methods for identification and validation of potential causes to root causes with the help of a few real life examples for effective Lean Six Sigma implementation.

The cause and effect diagram is the frequently adopted method for identifying potential causes out of a host of methods available for such identification. The method of validation depends on the practitioners’ knowledge on the relationship between cause and effect and controllability of the causes.

The roadmap thus evolved for the validation of root causes will be of great value to the practitioners as it is expected to help them understand the ground reality in an unambiguous manner resulting in a superior strategy for cause validation and corrective actions.