Purpose – The advent of recession at the beginning of twenty-first century forced many organizations worldwide to reduce cost and to be more responsive to customer demands. Lean Manufacturing (LM) has been widely perceived by industry as an answer to these requirements because LM reduces waste without additional requirements of resources. This led to a spurt in LM research across the globe mostly through empirical and exploratory studies which resulted in a plethora of LM definitions with divergent scopes, objectives, performance indicators, tools/techniques/methodologies, and concepts/elements. The purpose of this paper is to review LM literature and report these divergent definitions, scopes, objectives, and tools/techniques/methodologies. Design/methodology/approach – This paper highlights various definitions by various researchers and practitioners. A total of 209 research papers have been reviewed for the research contribution, research methodology adopted, tools/techniques/methodologies used, type of industry, author profile, country of research, and year of publication. Findings – There are plethora of LM definitions with divergent objectives and scope. Theory verification through empirical and exploratory studies has been the focus of research in LM. Automotive industry has been the focus of LM research but LM has also been adopted by other types of industries also. One of the critical implementation factors of LM is simultaneous adoption of leanness in supply chain. LM has become an integrated system composed of highly integrated elements and a wide variety of management practices. There is lack of standard LM implementation process/framework. Originality/value – The paper reviews 209 research papers for their research contribution, research methodology, author profile, type of industry, and tools/techniques/methodology used. Various characteristics of LM definitions are also reviewed.

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Purpose The purpose of this paper is to propose an integrated performance measurement framework to measure the effect of lean implementation throughout all functions of an organization. Design/methodology/approach The paper identifies the seven categories representing all organizational functions. These categories have been divided into 26 performance dimensions and key performance indicators (KPIs) for each performance dimension have been identified to measure lean performance. The interrelationship of each category with lean principles and/or lean wastes has been identified. KPIs are developed on the basis of identified criteria, frequency analysis of existing literature, and discussion with industry professionals. Finally, an integrated performance measurement framework is proposed. Findings The proposed framework evaluates the organization under seven categories – manufacturing process, new product development (NPD), human resource management, finance, administration, customer management, and supplier management. In total, 26 dimensions and 119 key performance indicators have been identified under the seven categories. Research limitations/implications The proposed framework is a conceptual framework and it is to be tested by empirical and cross-sectional studies. Originality/value The main novelty of the research is that the leanness of the organization has been measured throughout the supply chain of the organization in an integrated way. The various areas of measurement are manufacturing process, NPD, finance, administration, customer management, and supplier management. Further, the proposed KPIs are also categorized as qualitative or quantitative, strategic or operational, social or technical, financial or non-financial, leading or lagging, static or dynamic. This paper contributes to the body of knowledge in performance measurement.

Purpose The purpose of this paper is to review various themes of leanness, leanness assessment approaches, leanness assessment areas, and their evolution by a systematic literature review (SLR). Design/methodology/approach The eight types of literature review methodologies are identified and compared. The SLR is selected after critically analyzing the eight types of literature reviews. A four-phased SLR (i.e. plan, do, analyze/synthesize, and propose) has been carried out based on the peer-reviewed journal and conference articles on leanness assessment. Findings The existing literature on leanness assessment shows the lack of review-based papers on lean assessment. This study attempts to build a two-fold contribution to the field of leanness assessment: first, various types of themes, approaches, and assessment areas are identified; second, a framework for leanness assessment is proposed. The study shows that the research on leanness assessment is mainly empirical using qualitative judgment. The paper traces the changes in scope, areas, and approaches to leanness assessment. The scope of leanness assessment broadened from manufacturing process assessment to whole supply chain assessment including manufacturing process. The focus of earlier assessment was manufacturing and financial areas which now includes human resource, administration, new product development, suppliers, and customers also. Tool and technique based assessment has given way to outcome-based assessment using non-financial and qualitative parameters. Research limitations/implications One of the limitations of the study is that literature search was mainly focused on peer-reviewed articles published in English language only; therefore, some papers in others languages may have been missed. Apart from this, the SLR has been conducted for the manufacturing sector only. Practical implications The study is expected to be useful for the lean practitioners to identify the causes of reported lean failures. Moreover, the authors also expect that the conducted SLR will provide the passage to the practitioners for not only fostering the concepts on leanness assessment but also provide the vital and significant knowledge about the leanness assessment to the managers for enhancing organizational performance. Originality/value As per the authors’ knowledge, this is the first SLR on leanness assessment. It is expected that this paper will help the researchers working in the area of lean manufacturing to identify new areas of research.

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This paper develops a predictive and optimization model by coupling the two artificial intelligence approaches -artificial neural network and genetic algorithm -as an alternative to conventional approaches in predicting the optimal value of machining parameters leading to minimum surface roughness. A real machining experiment has been referred in this study to check the capability of the proposed model for prediction and optimization of surface roughness. The results predicted by the proposed model indicate good agreement between the predicted values and experimental values. The analysis of this study proves that the proposed approach is capable of determining the optimum machining parameters.