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The purpose of this paper is to propose the use of graph theoretic structural modeling for assessing the possible reduction in complexity of the work flow procedures in an organization due to lean initiatives. A tool to assess the impact of lean initiative on complexity of the system at an early stage of decision making is proposed.

First, the permanent function-based graph theoretic structural model has been applied to understand the complex structure of a manufacturing system under consideration. The model helps by systematically breaking it into different sub-graphs that identify all the cycles of interactions among the subsystems in the organization in a systematic manner. The physical interpretation of the existing quantitative methods linked to graph theoretic methodology, namely two types of coefficients of dissimilarity, has been used to evolve the new measures of organizational complexity. The new methods have been deployed for studying the impact of different lean initiatives on complexity reduction in a case industrial organization.

The usefulness and the application of new proposed measures of complexity have been demonstrated with the help of three cases of lean initiatives in an industrial organization. The new measures of complexity have been proposed as a credible tool for studying the lean initiatives and their implications.

The paper may lead many researchers to use the proposed tool to model different cases of lean manufacturing and pave a new direction for future research in lean manufacturing.

The paper demonstrates the application of new tools through cases and the tool may be used by practitioners of lean philosophy or total quality management to model and investigate their decisions.

The proposed measures of complexity are absolutely new addition to the tool box of graph theoretic structural modeling and have a potential to be adopted by practical decision makers to steer their organizations though such decisions before the costly interruptions in manufacturing systems are tried on ground.

The purpose of this paper is to study the impact of restructuring in the manufacturing system at the conceptual stage using graph theoretic model.

Some restructuring decisions are conceptualized which reflect the aim of the organization to gradually evolve the manufacturing system towards a leaner structure. This is achieved by way of defining simplified procedures so that lesser hindrance in terms of cycles of interactions is encountered. The restructuring decisions are represented by five restructured configurations of the manufacturing system, through gradual removal of appropriate interaction links. The graph theoretic models are developed for original configuration and each of the new restructured configurations and the resulting structural characterization information is used to compare the structure of restructured configurations with the original configuration. The value of the coefficient of dissimilarity of each of the new configurations with respect to the original configuration is obtained to have a quantitative estimate of the simplification that may be achieved by different contemplated restructuring decisions.

The present work shows that the restructuring decisions can be represented by different configurations in the form of schematic diagrams involving minor changes in the interaction structure among subsystems of the manufacturing system. The quantitative analysis using coefficient of dissimilarity for restructuring decisions indicated that there are varying levels of impact created by five comparable restructuring decisions considered in the study. The findings have a potential to guide the restructuring efforts by identifying a focus area that can produce greater impact of restructuring.

The findings are valid for a particular case manufacturing organization which does not involve itself in extensive design activity. The study is based on the assumption that the schematic diagram and graph theoretic model captured all the relevant influencing factors of the manufacturing system.

The study provides an easy to use methodology for the practical decision makers in manufacturing industry striving to improve the performance of their organization. It can provide the analysis of restructuring decisions at the conceptual stage itself without the necessity of disturbing the normal functioning of the organization. There is a scope for identifying focus areas where the restructuring may yield comparatively greater dividends.

The study of restructuring by representing it in the form of changes in interactions among subsystems of a manufacturing system and investigation of the impact of such restructuring efforts at the conceptual stage using graph theoretic model has been carried out for the first time.

A method for qualitative estimation of reliability of large and complex mechanical and hydraulic systems is presented. It is especially useful for comparison and optimum selection of the structure at the conceptual stage of design when no other information about the salient features or parameters of the system is known. The method permits the identification and analysis of critical paths, loops and subsystems causing failure under different causes and modes. The method is based on graph theory and the graph variants proposed as reliability measures are also modified to yield realistic and useful results. The concept of system graph introduced in the article for dealing with large systems appears to be the most appropriate for analysis, comparison, selection and reliability estimates at the beginning of the system′s design.

During the different phases of enterprise creation, entrepreneurial learning (EL) can be understood as an effective process. This study aims to find out the cause-and-effect relationships of the factors that are impacting EL.

This research has been conducted in two ways: first, the factors are identified through a systematic analysis of EL, and second, the cause-and-effect relationship among EL factors is analyzed using decision-making trial and evaluation laboratory, which is dependent on the opinion of experts. A network relationship matrix is also drawn from the measured factors.

A causal relationship has been established within the identified EL factors. Results indicate that educators and practitioners should focus and concentrate on the cause group-related factors, which are entrepreneurship education, entrepreneurial training, entrepreneurial competencies, experiences, family influence and role models. The remaining two, entrepreneurial perception and entrepreneurial willingness, are identified as being in the effect group. These two factors are affected and influenced by the cause group factors.

By recognizing the multidimensionality of EL, this study gives the chance to look at what it means to be an entrepreneur from both a personal and a social point of view, including learning styles, learning from mistakes and self-regulated learning. Future research is urged to build tools that accurately capture this crucial factors of EL, thus allowing the field to gain greater integration and information accumulation.

Researchers have previously described factors that influence EL, but to the best of the authors’ knowledge, this is one of few studies that depict the cause-and-effect relationship between EL factors. These factors are critical to the growth of talented entrepreneurs in both developed and developing countries for promoting an entrepreneurial culture.

The purpose of this paper is to attempt to integrate manufacturing system analysis to obtain system‐wide optimized solutions and to increase the level of comprehensiveness of the manufacturing system modelling and to develop method of characterization of manufacturing systems based on its structure.

Elements constituting the manufacturing plant and the interactions between them have been identified through a literature survey and have been represented by graph‐based model. The matrix models and the variable permanent function models are developed for carrying out decomposition, characterization and the total analysis.

Structural patterns and combination sets of subsystems interacting in various ways have been recognized as capabilities of manufacturing system in different performance dimensions. The permanent function of the manufacturing system matrix has been proposed as a systematic technique for structural analysis of manufacturing system. Also, the terms of permanent multinomial characterize the manufacturing systems uniquely and are highly useful for computational storage, retrieval, communication as well as analysis of the structural information of manufacturing system.

The structure‐based characterization technique developed has the potential of aiding the ongoing research activities in the field of benchmarking, and business process reengineering. The graph theory‐based methodology will serve as a framework to develop composite performance measures building on the performance measures of the individual elements of the manufacturing system graph in various dimensions.

Through the use of proposed methodology, a manufacturing manager will be able to make better informed decisions towards organizational efforts of improving the productivity and speed. For aiding several decisions, different “what‐if” scenarios may be generated with several structural modifications.

This graph theory‐based methodology is a novel mechanism to seamlessly integrate manufacturing system giving way to system wide optimization. The paper is an attempt to address the need for comprehensive and integrated analysis of the manufacturing system.

Reliability assessment does require an effective structural modelling approach for systems, in general and manufacturing systems are no exception. This paper aims to develop it for large manufacturing systems using graph models, a systems approach.

Structural graph models for reliability at various hierarchical levels are developed by considering a CNC cam shaft grinding machine. The system reliability expression is obtained by converting the reliability graphs into equivalent matrices, which helps to evaluate and analyse system.

Using the obtained reliability expressions at various hierarchical levels of the system, it is possible not only to evaluate its reliability from structure point of view but also to identify weak structural elements from reliability point of view.

The approach can be extended to include the influence of other parameters, such as human, component and environment, etc., on the system reliability.

The approach helps to design and develop manufacturing systems from reliability consideration by assessing their possible alternatives among these.

The suggested methodology is useful for reliability evaluation of large and complex manufacturing systems.

The purpose of this paper is to examine the influence of government support and technology usage on family business entrepreneurial intention. The paper also investigates the moderating impacts of gender on the family business entrepreneurial intention with its two predictors.

This paper has used both resource-based view and dynamic capability view theory as well as literature on family business entrepreneurship to develop the theoretical model. Later, the theoretical model has been validated using structural equation modelling (CB-SEM) with respondents from Indian family business enterprises. This study has used a purposeful and convenience sampling approach.

This study has shown the significance of technology usage as well as government support to improve the family business enterprise. The study highlights that there is a moderating impact of gender on the relationship between government support and technology usage with entrepreneurial intention in family business.

This study adds value towards body of literature in entrepreneurship, gender, and business, as well as family business literature. The study shows how gender acts as a moderator in case of family business entrepreneurship. The study is cross sectional in nature and has limited number of respondents from India. Thus, the findings cannot be generalizable.

This study is a unique study as it investigates the influence of both government support as well as technology usage by the family business firms for entrepreneurial intention. The proposed theoretical model has a high predictive power which makes the model effective. Moreover, this study also examines the moderating impacts of gender on entrepreneurial intention in the family business which adds value to the existing body of knowledge.

The theory-building around the quality of human resources has received extensive attention in recent years. Numerous quantitative studies discuss and test theories related to total quality management and human resource linkages. The study aims to understand interlinkages of quality and human resources using Interpretative Structural Modeling (ISM) methodology and DEMATEL.

This paper uses ISM methodology to examine the interrelationship between the identified variables and the DEMATEL approach to find cause–effect relationships. An integrated approach helps managers for better total quality management (TQM) implementation. This study further extended using Total Interpretative Structural Modeling (TISM).

The integrated approach of ISM and DEMATEL shows that leadership development, hiring process and training development become most important for TQM implementation. The outcome of ISM shows customer satisfaction and corporate image are depending on other practices, where DEMATEL analysis revealed that eight practices cause and remaining are effective practices.

This research's integrated approach helps the firm identify essential practices, and further interdependency can be developed from cause and effect analysis. The study also provided a novel approach to implementing TQM practices.

This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.

The experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.

The results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speed V_c = 80 m/min, feed rate f = 0.05 mm/rev. and depth of cut a_p = 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.

The research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

The purpose of this paper is to identify the key enabler for total productive maintenance (TPM) implementation in Indian small and medium enterprises (SMEs) by using graph theoretic approach (GTA). There are certain enablers for TPM implementation which helps the organization to implement it successfully. It is very essential to identify the nature and impact of these key enablers.

A large number of the enablers (27) have identified for TPM implementation in Indian SMEs from the available literature, questionnaire survey and expert opinion. These TPM enablers have categorized into six major categories.

In this research work, the intensity of identifying enablers has been calculated to show their impact or influence in TPM implementation. The value of intensity of TPM enablers shows the role or impact of individual enabler in the implementation of TPM in Indian SMEs.

This study provides an easy-to-use methodology for the practical decision makers in the manufacturing industry to improve their performance by implementing TPM in Indian SMEs. A detailed methodology has prepared to identify the enablers for TPM implementation in Indian SMEs by using GTA. This study also explains that how to check the feasibility of an organization to implement TPM in Indian SMEs successfully.

TPM is an improvement concept which holds the potential to improve manufacturing organizations, but its implementation is not easy in Indian SMEs. The reason behind the unsuccessful implementation of TPM in most of the organizations is the ignorance of impact of innumerable enablers and barriers.