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The purpose of this paper is to report a study in which analytic hierarchy process (AHP) has been used for selecting the best concept in lean environment.

There existed a need for the case organization to identify the best concept from the perspective of lean manufacturing. The concept selection problem is a typical multi‐criterion decision‐making problem. AHP judges and selects the elements/concepts which have a greater influence on the pre‐determined objective. In this study, AHP has been used for selecting the best concept.

The validation indicated that AHP is an effective approach for enabling best concept selection, thereby improving the leanness of the organization.

The implementation study has been carried out by substituting the data gathered from only one manufacturing organization. Yet the findings and contribution of this research work would be useful to the leaders of majority of the manufacturing companies situated in the world.

The usage of the approach will indicate that AHP enables the best concept selection in advanced manufacturing environments.

A case study has been reported to indicate the feasibility of selecting the best concept in a lean environment. Hence, the contributions are original.

This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.

An integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.

The ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.

This paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.

It provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

The purpose of this paper is to measure competitive service quality (SQ) performances of domestic full service airlines in India by providing a framework based on analytic hierarchy process (AHP), in order to benchmark their SQ thus, enhancing competitiveness and gaining competitive advantage.

The present study has used the AHP methodology to benchmark the SQ of airlines in India. Subsequently, competitive SQ gap analysis is performed to evaluate and compare strength and weakness of focal firm (Airline “B”) against its competitors.

In this research work, total of 23 SQ attributes and five dimensions have been identified based on extensive literature review, focus group brainstorming and experts opinion from the Indian airline industry. The study reveals that air travelers rate assurance as the most important criteria and safety as the most important sub criteria followed by on time performance, performing the services right, the first time and remedial process for delayed or missing baggage. Furthermore, based on AHP methodology, the result shows that Airline “A” has emerged as a market leader and is considered as a benchmark airline.

This framework will help airline management and policy makers to identify area of service improvements and identify SQ gaps with respect to the benchmark airline. This will help in formulating suitable competitive strategies for SQ improvements, thus gaining competitive advantage.

In this research work, AHP-based SQ framework have been applied in Indian domestic aviation industry for competitive SQ benchmarking which is a novel contribution, thus widening the existing knowledge base in aviation SQ literature.

The purpose of this paper is (1) to review, analyze and assess the existing literature on lean tools selection studies published from 2005 to 2021; (2) to identify the limitations faced by previous studies; and (3) to suggest future works that are necessary to facilitate the selection of lean tools.

A systematic approach was used in order to identify, collect and select the articles. Several keywords related to the selection of lean tools were used to collect articles from different Scopus indexed journals. Next, the study systematically reviewed and analyzed the selected papers to identify the lean tools' selection method and discussed its features and limitations.

An analysis of the results showed that previous studies have adopted two types of methods for selecting lean tools. First, there are various traditional methods being used. Second, multi-criteria decision-making (MCDM) methods were commonly used in previous studies, such as the multi-objective decision-making method (MODM), single multi-attribute decision-making (MADM) methods and hybrid (MCDM). Moreover, the study revealed that the lean tools' selection methods in previous studies were based on evaluating the relationship between either lean tools and performance metrics or lean tools and waste, or both.

In terms of its theoretical value, the study is considered as an extension of the previous researches performed on this topic by determining and analyzing the features of the most selection methods of lean tools. Unlike previous review papers, this review had considered discussing and analyzing the characteristics and limitations of these methods. Section 2.2 of this paper reviewed some of the categories of MCDM methods as well as some of the traditional methods used in the selected previous studies. Section 2.1 of this paper explained the concept of lean management and its application benefits. Further, only three sectors were covered by the previous studies in this review paper. This study also provided recommendations for future research. Therefore, it provided researchers with a good conception of how to conduct the studies on lean tools selection. Besides, knowing the methods used in previous studies can help researchers develop new methods to select the best set of lean tools. That is, this study provided and advanced the existing knowledge base for researchers concerning lean tools selection, especially there is limited availability of review papers on this topic. Moreover, the study showed researchers the importance of the relationship between lean tools and indicators or/and performance indicators to determine the appropriate set of lean tools so that the results of future studies will be more realistic and acceptable.

Practically, manufacturers face a significant challenge when selecting proper lean tools. This study may enhance managers, manufacturers and company's knowledge to identify most of the methods used to choose the best set of lean tools and what are the advantages, disadvantages and limitations of these methods as well as the latest studies that have been adopted in this topic. That means this study can direct companies to prioritize the application of lean tools depending on either the manufacturing performance metrics or/and manufacturing wastes so that they avoid incorrect application of lean tools, which will add more non-value added activities to operations. Therefore companies can decrease the time and cost losses and enhancing the quality and efficiency of the performance. Correctly implementing the best set of lean tools in companies will lead in general to correctly applying lean management in corporations. Therefore, these lean tools can boost the economic aspect of companies and society through reducing waste, improving performance indicators, preserving time and cost, achieving quality, efficiency, competitiveness, boosting employee income and improving the gross domestic product. The correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. Besides, the correct lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right selection of lean tools will have positive effects on both the environment and society. The study may also encourage manufacturers and researchers to adopt studies on lean tools selection in small- and medium-sized companies because the study referred to the importance and participation of these kinds of companies in a large proportion of the economy of developing countries. Further, the study may encourage some countries that have not previously adopted this type of study, academically and industrially to conduct lean tools selection studies.

As mentioned previously, the correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. The proper lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right choice of lean tools will positively affect both the environment and society.

The study expanded the efforts of previous studies concerning lean management features. It provided an accurate review of most lean tools selection studies published from 2005 to 2021 and was not limited to the manufacturing sector. It further identified and briefly described the selection methods concerning lean tools adopted in each paper.

This paper aims to guide about prioritisation and ranking of the solutions and overcoming barriers to facilitate the adoption of Lean Six Sigma (LSS) by using a hybrid framework.

It identifies LSS barriers and solutions to facilitate LSS adoption through literature review and by involving subject experts. The study makes use of fuzzy set theory and proposes a fuzzy analytical hierarchy process (AHP)-modified TOPSIS (technique for order preference by similarity to ideal solution) framework. It uses sensitivity analysis to establish framework robustness.

The key findings of this techno-managerial study are identification and prioritisation of 27 LSS barriers and 22 solutions to overcome adoption challenges, proposition and usage of fuzzy AHP-modified TOPSIS framework, guidance regarding where to focus for facilitating LSS adoption and ensuring robustness using sensitivity analysis, which establishes insignificant deviation in rankings when criteria weights are altered.

Some biasness and subjectivity may exist during pairwise comparisons as human judgements are involved.

Handling a hybrid solution like LSS is never easy. It is expected that the study will help industry professionals to plan their LSS adoption attempts effectively. Guidance regarding LSS barriers will assist in observing necessary precautions to avoid failures. It will open up new research fronts for researchers also.

Literature is full of studies regarding LSS barriers and its rankings. It is very rare to witness a study like ours, which discusses the barriers and links with solutions and its prioritisation. Proposed hybrid framework for a hybrid techno-managerial approach such as LSS is unique and acts as the roadmap for smooth implementation.

Many projects focus on the reliable operation of the activities in the project. Any failure in the process activities leads to major problems resulting in waste, defects, equipment damage, which has a direct impact on the consumers. In addition, Lean Six Sigma (LSS) is not new to this issue. LSS projects have faced an interruption in the process flow and unforeseen defects. Therefore, the purpose of this paper is to identify the vital failure factors of LSS projects.

Through extant literature review, the researchers found 44 critical failure factors (CFFs) of LSS. Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) SIMOS approach, the decision makers’ (DMs) rating and weight for each factor were collected. Moreover, the study was conducted in both the manufacturing and service industries to identify the impact of CFFs in LSS projects.

CFFs and their evaluation have received little attention in the literature. Most of the previous studies deal only with the identification of the success factors in general. Therefore, the study identified 44 CFFs and ranked them through DMs. In addition, the TOPSIS SIMOS approach ranked the vital failure factors enabling the management to avert the LSS project from failures.

The study focused on project failures due to CFFs of LSS. Nevertheless, it did not consider other failure factors of project and knowledge management. Further, the sample used to test the approach was considerably small. Therefore, the study can be repeated with significant samples and the vital failure factors compared.

In real-life application, all the parameters in the LSS project need to be understood in a better manner. In such a condition, the practitioner needs to know that the project never fails due to the CFFs and TOPSIS SIMOS approach can prevent the LSS project failures.

The study applied TOPSIS SIMOS approach to rank the CFFs in an LSS project, which is first of its kind and aids the practitioners to make the right decisions in the business environment.

The purpose of this research paper is to identify the enablers for Lean implementation in the manufacturing sector, to establish a relationship among them using interpretive structural modeling (ISM) and to rank them using interpretive ranking process (IRP).

The research paper presents a blend of theoretical framework and practical applications. In the paper, eight enablers of Lean production are identified from literature survey and experts’ opinion. These include 5S, value stream mapping (VSM), just in time, single minute exchange of die, computer-integrated manufacturing, concurrent engineering, training and enterprise resource planning. ISM is used to obtain a structural relationship among these enablers of Lean. MICMAC analysis is used to identify the driving power and dependence of the variables. Further, IRP is used to rank the lean enablers with respect to key performance areas.

The ISM- and IRP-based models indicate that “training” is the most significant factor for the Lean implementation process in manufacturing sector. The MICMAC analysis also shows that “training” has the maximum driving power and the least dependence and hence has strong managerial significance. The management should place high priority on tackling this criterion. VSM occupies the top level in the ISM hierarchy, indicating that all other Lean enablers should act in unison to make VSM implementation a success.

Enablers are the building blocks for deployment of the Lean concept. To know the key enablers and relationship among them can help many organizations to develop Lean competencies. This study is perhaps among the first few that focuses on two modeling procedures based on interpretive logic, i.e. ISM and IRP. The paper provides useful insights to the Lean production implementers, consultants and researchers.

The purpose of this paper is to investigate, through a comparative analysis, the applicability of lean manufacturing practices, such as value stream mapping (VSM), for productivity improvement in recycling centres (RCs) aided by multi-criteria decision analysis.

The study is carried out in five RCs that sort the municipal solid waste of Porto Alegre, one of the main cities in Brazil. Since all of the centres present their labour composed by poor communities’ members, cultural and social characteristics may represent an incremental challenge for lean implementation. Further, these centres are organised in cooperatives, in which decisions are taken through a participatory way and all their members are entitled to vote, undermining and retarding the decision-making process.

The integration of a multi-criteria decision-making tool to the lean practices enables the prioritisation of improvements, complementing the final stage of VSM. In particular, this contribution becomes especially important in cooperatives managed by community, where decisions are often complex and time-consuming. Finally, despite the increasing pressure for better performance of RCs, the existent mindset is still far from the private sector, where lean practices were conceived. Further, the findings suggest that, despite processes similarities, it is not feasible to declare the existence of a one-best practice to such scenario.

In theoretical terms, the authors demonstrate through a multi-case study the adequacy of analytic hierarchy process as a decision analysis tool complementary to the VSM, enabling a broader perspective about this subject. Concerning the practical contribution, the comprehension of the adaptation needs for lean practices implementation within the production context of solid waste RCs provides a framework with guidelines for this sector, when incorporating lean activities. Lean practitioners and eventual municipal authorities involved in improving productivity of community-managed RCs might benefit from this framework, since they will be able to emphasise the development of recommended and already tested lean practices that tend to improve their operational performance.

The purpose of this paper is to conceptualize the integration of total productive maintenance (TPM) and ISO 9001 certification by contributing a model named as TPM 9001:2008.

In the beginning of the paper, the origin, growth and capabilities of TPM and ISO 9001 certification in enabling the organizations to perform at world class level are appraised by citing research outcomes reported in literature arena. The information and knowledge thus gathered from literature arena are used to conceptualize TPM 9001:2008 model. Through this conceptualization, the eight TPM pillars are fitted into the five major clauses of ISO 9001:2008 standard. In order to illustrate this conceptualization, the contents of a sub-clause of TPM 9001:2008 model are presented and the rationale behind designating it is appraised.

TPM 9001:2008 model brings out synergy from the two renowned world class strategies namely “TPM” and “ISO 9001 certification”.

The paper points out that the practical validity of TPM 9001:2008 model shall be established by conducting real time case studies in various organizations.

This paper presents a unique approach for integrating TPM elements with ISO 9001:2008 standard based quality management system, as a single framework benefiting the contemporary organizations.

The purpose of this paper is to classify the main barriers related to the implementation of lean supply chain management (LSCM) and prioritize its main practices. A case study approach was conducted to obtain values for the intensity of the relationship between LSCM practices and barriers to mitigate or even anticipate difficulties in its implementation.

The case study in a company in southern Brazil that is in lean implementation is used for conducting this research. The methodology was structured in three steps, namely, classification of the main barriers through risk analysis, selection of LSCM practices appropriate to the company context and ranking and prioritization of the main practices of LSCM related to the barriers to lean implementation.

As a result, with the combination of two approaches, failure mode and effect analysis (FMEA) and analytical hierarchical process (AHP), it was possible to obtain values for the intensity of the relationship between LSCM practices and barriers. From the 12 barriers, 5 reached a high-risk degree that can be mitigated, and among the 18 practices found, 7 have the potential to be implemented.

This research allows direct efforts to continuously improve the supply chain to mitigate or even anticipate difficulties in its implementation. The proposed methodology, combining FMEA and AHP is easy to apply and understand, allowing managers and professionals to replicate it in the context of their supply chain and verify results similar and comparable to those obtained here.