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Continued quest for business improvement in terms of enhanced productivity and cost cuts is the most valued strategic function in an organization. Towards this endeavor, there have been evolutions of many problem-solving techniques like Lean, quality control (QC) tools, Six Sigma, total productive maintenance (TPM), etc. This paper introduces a different problem-solving methodology for quality improvement – prepare, measure, define, establish, control and stabilize (PMDECS) approach of Red Bin Analysis (RBA) – and presents empirical evidence of its effectiveness in eliminating the defectives at source (parts per million [PPM]) and improving the process capability (Cp).

An attempt has been made to compare RBA with the Six Sigma methodology in terms of number of defects, defectives, process capabilities, project duration, etc. Data validation with more than 2000 data points was conducted based on empirical data collected over multiple problem-solving projects conducted in six manufacturing industries of India to compare the effectiveness of both the methods. Finally, fuzzy AHP (analytical hierarchy process) model was proposed to identify the Quality Improvement Index for both the methods to address the manager’s dilemma in selecting an appropriate problem-solving method.

The paper provides empirical insights in establishing that the PMDECS approach of RBA is at par and sometimes better for problem-solving if the problem is not chronic and is at the initial stages, it requires less duration than Six Sigma projects and except casting process and it can yield better results in case of PPM rejection or Cp/Cpk improvement in other processes.

Because of the chosen research approach, the research results may lack generalizability. This research has been specifically conducted in automotive manufacturing industries. Therefore, researchers are encouraged to test the proposed propositions further.

The paper includes implications for the usage of alternative problem-solving methods, like PMDECS approach of RBA.

This paper intends to compare how the results of six sigma projects in manufacturing industries are effective against a different methodology, PMDECS approach of RBA.

The purpose of this paper is to present a systematic review and analysis of existing research articles on new product development (NPD) published in the 12-year period starting from 1998 to 2009.

To explore the articles related to NPD, four key words namely new product, product design, product development and product innovation were used in combination of title or abstract or keyword of the articles through several knowledge databases. The abstracts of journal papers were read and a decision as to whether article belongs to any NPD research issue or not was made. In total, 1,127 research articles were categorized systematically and then analyzed on various principal NPD information groups.

Analysis of selected articles led to a certain level of dispersion in the publication of NPD research in different journals. It is found that more attention needs to be on knowledge and creativity management, communication and information transfer in any NPD process.

By observing extended literature from authors reviewing articles from various journals, growth in research, and variety of topics covered in NPD, a broad systematic multi journal review of NPD literature is clearly overdue. The authors have developed a comprehensive listing of publications on NPD where they have classified the surveyed papers according to various principal NPD information groups like: published year, NPD research stream, type of organization studied (industrial/consumer/service), level of innovation (high/moderate/low), NPD focus on frameworks, performance perspective (success, failure or both), NPD research design (conceptual/empirical and qualitative/quantitative) and NPD relevant best practice element. Based on the classification scheme, the issues were analyzed from the system's perspective and their implications to NPD research.

Quality function deployment (QFD) has been used to translate customer requirements into engineering characteristics of a product, while benchmarking was developed to search for the best industry practices, which will lead to exceptional performance through the implementation of these best practices. However, no attempt has been made to integrate QFD with benchmarking to identify the best practices of QFD model. This paper aims to classify the QFD models and thereby applying benchmarking process to propose the best practices of QFD model.

The fundamental benchmarking model developed by Camp has been used to benchmark the existing QFD models available in the literature.

Benchmarking the QFD models revealed about 36 QFD steps in the first phase of the house of quality. The tools used in solving for each practice are also reported.

The proposed model is conceptual and it requires validation by implementing the same in an organization to understand its effectiveness.

Utilizing the benchmarking process to develop the best practices of QFD model is an original concept.

The purpose of the study is to study the relation between new product development (NPD) innovation and NPD best practices in an organization with respect to NPD performance in the backdrop of Indian manufacturing industry.

Performance indices are developed based on NPD innovation and NPD best practices in an organization. Based on the developed performance indices, a cluster typology or classification of surveyed organizations is conducted. Different hypotheses are generated and tested to chet1ck the relation between NPD best practices and NPD innovation in an organization with respect to NPD performance in the Indian manufacturing industry.

The following results were obtained: there is a positive effect on NPD performance for those organizations that strongly implement NPD best practices; the stronger the NPD innovation, the higher the NPD performance; and stronger organizations' ability for NPD innovation has positive relationship with NPD best practices. Hence, it is proven that, “the stronger the NPD innovation in an organization, with defined NPD best practices, the better the NPD performance”.

According to the author’s knowledge, no study is reported in literature which addresses the effect of NPD best practices and NPD innovation in an organization with respect to performance in the Indian manufacturing industry.

The purpose of this paper is to conduct an empirical investigation on the new product development (NPD) practices in Indian manufacturing industries. The NPD best practices constructs are identified from the literature and then an effort have been made to statistically establish the underlying principal components of NPD practices by checking their reliability and validity for the case of Indian manufacturing industry.

In all, 96 NPD best practices constructs are identified from literature articles published between 1998 and 2009. Principal component analysis (PCA) is conducted to establish the seven components of NPD practices. Cronbach's α values are computed to measure internal consistency or reliability of the established components of NPD practices. Further, confirmatory factor analysis is conducted on the established measurement model to test a hypothesized factor structure through construct validity, convergent validity and divergent validity.

The PCA of NPD best practices identified the seven underlying components (latent variables) namely “NPD strategy,” “NPD support system,” “product portfolio management,” “NPD team,” “NPD tools,” “product launch” and “concept generation.” In NPD strategy, Indian manufacturing companies are highly inclined toward cost reduction, cycle time reduction, competitive advantage and fast follower strategies. All NPD support system constructs are information technology dependent tools which require hardware, software and databases to support it. Indian manufacturing organizations are fundamentally concentrating on right balance of portfolio through improvements in the current products, cost reduction and additions to existing lines by using modular architectures and the reliable and valid NPD tools are FMEA, six sigma/quality management, DFMA/DF’X and QFD.

To the best of the author's knowledge, this research represents the first attempt to investigate empirically the NPD practices in Indian manufacturing industry.