Application of total interpretive structural modelling (TISM) for analysis of factors influencing sustainable additive manufacturing: a case study

2019 ◽  
Vol 25 (7) ◽  
pp. 1198-1223 ◽  
Author(s):  
Rohit Agrawal ◽  
Vinodh S.

Purpose The purpose of this study is to develop a structural model based on total interpretive structural modelling (TISM) approach for analysis of factors influencing sustainable additive manufacturing (AM). Design/methodology/approach A total of 20 factors influencing sustainable AM are identified on the basis of literature review. Appropriate inputs from experts are obtained and TISM model is developed. Also, cross-impact Matrix multiplication applied to classification (MICMAC) analysis is carried out to categorize the factors. Findings Based on TISM model, “Flexibility in manufacturing”, “Time to develop new product” and “Local availability of technology” are found to be the dominant factors. MICMAC analysis indicates that 10 factors belong to driving and 10 factors belong to dependent category. Research limitations/implications In the present study, 20 factors have been considered. In future, additional factors can be considered to deal with technological advancements. Practical implications The conduct of the study will enable AM experts to systematically analyze the factors influencing sustainable AM. Originality/value The development of structural model for analysis of factors influencing sustainable AM manufacturing is the original contribution of authors.

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
S. Logesh ◽  
S. Vinodh

Purpose This paper aims to focus on developing a theoretical framework for the analysis of factors influencing additive manufacturing (AM) in the health-care domain. Design/methodology/approach A total of 18 factors are considered through extensive literature review and the relationship between each factor is studied using total interpretive structural modeling (TISM) and the model is logically developed. TISM model is developed using appropriate expert inputs. In addition, cross-impact matrix multiplication applied to classification (MICMAC) analysis is conducted to group the factors. Findings It was found that “ease of design” and “research and development” are the two most important factors with the highest driving power and dependencies. Through MICMAC analysis, the significance of factors is studied. Practical implications The study has been done based on inputs from academic experts and industry practitioners. The inferences from the study have practical relevance. Originality/value The development of a structural model for the analysis of factors influencing AM in the health-care domain is the original contribution of the authors.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aadithya B.G. ◽  
Asokan P. ◽  
S. Vinodh

Purpose The purpose of the paper is to depict a study on analysis of barriers to lean adoption in fabrication industry using interpretive structural modelling (ISM). Design/methodology/approach From the literature review, 22 barriers to lean adoption in fabrication industry have been recognized . Self-structure interaction matrix has been developed based on expert opinion. Computational steps of ISM are being done to develop the structural model. cross-impact matrix multiplication applied to classification (MICMAC) analysis is being done to group the barriers into four types. Findings Based on the study, it has been found that “lack of knowledge about lean (philosophy, principles, tools)”, “lack of top management support and commitment” and “poor leadership” are found to be the principal barriers. MICMAC analysis indicated that number of driving, dependent, linkage and autonomous barriers are 9, 8, 4 and 1, respectively. Practical implications The study has been executed based on the inputs from industrial practitioners and hence the inferences are found to have practical relevance. Originality/value The study is an attempt to analyze the barriers for lean concepts adoption in fabrication kind of industry.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vishal Ashok Wankhede ◽  
Vinodh S.

Purpose The purpose of this paper is to develop a model based on the total interpretive structural modeling (TISM) approach for analysis of factors of additive manufacturing (AM) and industry 4.0 (I4.0) integration. Design/methodology/approach AM integration with I4.0 is attributed due to various reasons such as developing complex shapes with good quality, real-time data analysis, augmented reality and decentralized production. To enable the integration of AM and I4.0, a structural model is to be developed. TISM technique is used as a solution methodology. TISM approach supports establishing a contextual relationship-based structural model to recognize the influential factors. Cross-impact matrix multiplication applied to classification (MICMAC) analysis has been used to validate the TISM model and to explore the driving and dependence power of each factor. Findings The derived structural model indicated the dominant factors to be focused on. Dominant factors include sensor integration (F9), resolution (F12), small build volumes (F19), internet of things and lead time (F14). MICMAC analysis showed the number of driving, dependent, linkage and autonomous factors as 3, 2, 12 and 3, respectively. Research limitations/implications In the present study, 20 factors are considered. In the future, additional factors could be considered based on advancements in I4.0 technologies. Practical implications The study has practical relevance as it had been conducted based on inputs from industry practitioners. The industry decision-makers and practitioners may use the developed TISM model to understand the inter-relationship among the factors to take appropriate measures before adoption. Originality/value The study on developing a structural model for analysis of factors influencing AM and I4.0 is the original contribution of the authors.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nishtha Agarwal ◽  
Nitin Seth

PurposeThe study tries to identify the barriers influencing supply chain resilience and examine the inter-relationships between them. These relationships are built on the basis of how one barrier drives or is driven by the changes in another barriers.Design/methodology/approachIn the first phase, literature review and with due discussion with experts, the barriers have been identified and shortlisted for an Indian automotive case company. In the second phase, total interpretive structural modelling (TISM) has been applied to examine inter-relationships between the barriers for an Indian automobile case company. Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis has also been performed to analyse the driving and dependence power of the barriers.FindingsIn total, 11 barriers are identified from the first phase of the study. In the second phase, the TISM digraph is created which qualitatively explains the reason behind how one barrier leads to another. MICMAC analysis classifies these variables in four clusters namely autonomous, linkage, dependent and independent. These clusters characterise the barriers based on their driving and dependent power which helps managers in strategically tackling them while taking understanding from the TISM digraph.Research limitations/implicationsThree research implications can be made from the study. First, a comprehensive definition of supply chain which helps in understanding of resilience based on disruption phases and recovery. Second, 11 barriers are identified which hinder resilience in automotive sector. Their relationships are modelled using TISM which also gives why a particular relationship exists. Last, MICMAC analysis classifies barriers based on how high or low the driving and dependence power exists.Practical implicationsThe study offers significant implications for supply chain managers helping them in building resilience by identifying barriers and reducing their effect. Barriers are identified for case company which might help managers to tackle them during disruptions. The final TISM digraph depicts the “why” between the inter-relationships between the barriers to resilient supply chains. TISM shows that non-commitment of top management is the major root barrier which has been causing the other problems. MICMAC analysis is also performed along with discussion as to how autonomous, linkage, dependent and independent barriers can be tackled to build resilience.Originality/valueTISM is considered as an effective methodology for conceptual framework development as it also explains “why” between the relationships besides explaining the “what” as against ISM. Identification and understanding of barriers and their interrelationship will help supply chain managers to analyse the influence and inter-dependence of barriers on the resilience of the supply chain. Such understanding will help in mitigating/averting these barriers hence improving the resilience capability. It also adds to the knowledge base in the area of supply chain resilience where several authors have pointed the lack of research.


2021 ◽  
Author(s):  
Slim ZIDI ◽  
Nadia Hamani ◽  
Lyes Kermad

Abstract The reconfiguration of supply chain is becoming a crucial concept used to deal with market disruptions and changes such as COVID 19 pandemic, demand uncertainty, new technologies, etc. It can be defined as the ability of the supply chain to change its structure and functions in order to adapt to new changes. Its assessment requires an understanding of its quantitative factors to provide indicators that are easy to interpret. Effective reconfigurability assessment can be achieved by measuring quantitatively its six characteristics (modularity, integrability, convertibility, diagnosability, scalability and customization). This paper aims at identifying the quantitative factors of each characteristic and their inter-relationships by using Total Interpretive Structural Modelling (TISM). The structural model obtained by TISM is applied to understand the dependency quantitative factors. Based on TISM results, a classification of quantitative factors is determined using « Matrice d'Impacts Croisés, Multiplication Appliquée à un Classement » (MICMAC) analysis. This paper may be helpful to understand the previously mentioned characteristics of reconfigurable supply chain in order to facilitate the measuring and the assessment of reconfigurability.


2017 ◽  
Vol 14 (3) ◽  
pp. 256-269 ◽  
Author(s):  
Adarsh Anand ◽  
Gunjan Bansal

Purpose The “quality” of any product or service defines the agility of the product and its life cycle in dynamic environment. The demand of high “quality” becomes an imperative concern, when “software” is acting as a product or a service. Since the nature of the software is intangible and more complex, therefore the assurance of providing accurate results is anxiety for companies. The overall quality of the software is based upon many individual factors (or attributes) that makes software reliable, inclined and a long-lasting product in the marketplace. But how these factors can influence each other is significant to identify. Therefore, the purpose of this paper is to study the quality aspect of the software and analyse the interrelationship of impactful attributes. Design/methodology/approach The analysis has been done through responses sought from software development teams/clients in India. The questionnaire related to the software quality was administered to the sample population. Interconnection among impactful characteristics has been analysed by using a qualitative technique called interpretive structural modelling (ISM). The driving and dependency of the attributes under consideration has been classified using cross-impact matrix multiplication applied to classification (MICMAC) analysis. The procedure of applying ISM method has been automated and provided it as package “ISM” using R software. Findings In general, it is very complex job to determine the most impactful attribute of software quality. By applying ISM and MICMAC analysis on the set of attributes under consideration, it has been found that “reliability” along with “usability” and “performance” is the most influential attribute of software quality and preferred most. Research limitations/implications Though ISM provides an organized modelling framework yet its results are considered less statistically significant. Therefore, it would be interesting to concatenate the present findings with the findings of any analytical methodology; which gives statistically significant results. Practical implications The present proposal deals with the interpretation of the software quality attributes and their contextual relationship but with more effective and efficient manner. It can help management to understand the complexity of relationship amongst attributes (which are quality attributes here) more accurately and precisely. Since today is an era of automation, the manual part is being substituted so as to reduce the labour cost, improve safety, security and product quality to increase production. This study is, therefore, an effort and a helping hand in making the hassle free calculations for obtaining intermediate matrices and doing eventual calculations. Social implications n numbers of parameters can be selected to analyse the interrelationship of any project/study. Eradication human errors in applying transitivity law or applying any other operation in solving problem. The package created here can save precious time of users. Provides well-formatted and readable excel output files that make interpretation easier. Originality/value Software is one such product/service which plays a significant role in this high-technological world, where each and every firm try their best to be on the top of the list of consumers’ preference. For this purpose, companies reduce manual efforts by converting it into qualitative software that provides deliverables in a systematic manner. Therefore, it becomes imperative to study various interrelated quality attributes of the software. On the similar platform, ISM is a widely used technique and just to provide a helping hand in quantification of the qualitative attributes this paper facilitates the readers with algorithm developed using R software.


2020 ◽  
Vol 15 (3) ◽  
pp. 919-932
Author(s):  
Arun Palaniappan ◽  
S. Vinodh ◽  
Rajesh Ranganathan

Purpose The purpose of this paper is to report the analysis of factors influencing additive manufacturing (AM) application in the food domain. Design/methodology/approach Based on literature review, 16 factors are being considered in the study. Interpretive structural modelling is used as a modelling approach. The derived structural model indicates the dominant factors. Matriced’ impacts croises-multipication applique and classment (cross-impact matrix multiplication applied to classification) (MICMAC) analysis is being done to group the factors. Findings Based on the study, it has been found that raw material usage, the shelf life of food, demand for the food and accuracy are dominant factors. MICMAC analysis indicated that number of driving, dependent and linkage factors are 6, 4 and 4, respectively. Research limitations/implications In the present study, 16 factors are being considered. In future, additional factors could be considered to deal with advancements in the food domain. Practical implications The study has been executed in discussion with practitioners in AM, and hence derived inferences have practical validity. Food making has become more agile with 3D printer and has become sensitive to customer demand. Social implications Social implications are primarily highlighted by the aspect of controlling the exact amount of nutrients corresponding to the application of food. In certain commercial applications, people can customize their shape and ingredients to be injected into the food. Originality/value The development of a model for the analysis of factors influencing AM in the food domain is the original contribution of the authors.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aqueeb Sohail Shaik ◽  
Sanjay Dhir

Purpose The purpose of this study is to explain the interrelationships between the elements of strategic thinking, technological change and strategic risks. The main objective of this research is to identify the hierarchy for the elements of thinking, technological change and strategic risk and also to identify the driving powers of these elements. Design/methodology/approach The methodology used in this study is modified total interpretive structural modelling and MICMAC analysis which gives the interrelationships and also the driving powers of the elements by analysing the relationships between the elements from the existing literature. This method helps us in answering/understanding the “what”, “how” and “why” of the research. Modified total Interpretive structural modeling is considered in this study, which helps in doing both the paired comparisons and transitivity checks simultaneously. A digraph is constructed at the end of the analysis, which shows the links between the elements, and a driver dependence matrix is constructed, which shows the driving powers. Findings This study gives an understanding of the role of the elements, the relationships between them and the hierarchy of addressing these elements, and also the driving and dependence power. Findings of this research give us an understanding of how strategic thinking/technological change/strategic drives the performance of the firm. Research limitations/implications This study is conducted with the help of existing literature; this can be further extended by considering the expert opinion. Practical implications The model explains the direct and transitive links of the elements and the strength of the relation between them, which helps the researchers and the practitioners to understand the driving power and importance of these constructs. It also helps us to understand the role of these elements and, if implemented in an organisation, which elements need to be prioritised for enhancing the performance of the firm. Originality/value Research done in the past has individually analysed the elements effecting strategic thinking; this study identifies the relationships between the elements of all three constructs and helps in understanding the levels of hierarchy.


2019 ◽  
Vol 15 (1) ◽  
pp. 297-317 ◽  
Author(s):  
Prakash Agrawal ◽  
Rakesh Narain ◽  
Inayat Ullah

Purpose Digital supply chain (DSC) is an agile, customer-driven and productive way to develop different forms of returns for companies and to leverage efficient approaches with emerging techniques and data analytics. Though the advantages of digital supply chain management (DSCM) are many, its implementation is quite slow for several reasons. The purpose of this paper is to identify the major barriers which hinder the adoption of DSC and to analyse the interrelationship among them. The barriers of DSC are explored on the basis of existing literature and experts’ opinion. Design/methodology/approach This paper uses the interpretive structural modelling (ISM) approach to develop a hierarchical structural model which shows the mutual dependence among the barriers of DSC. Cross-impact matrix multiplication applied to classification analysis was performed to represent these barriers graphically on the basis of their driving power and dependence. Findings The research demonstrates that the barriers “no sense of urgency”, “lack of industry specific guidelines”, “lack of digital skills and talent” and “high implementation and running cost” are the most significant barriers to digital transformation of supply chain. This paper also suggests some managerial implications to overcome the barriers which hinder the implementation of digital transformation of supply chain. Practical implications This paper assists managers and policymakers to understand the order in which these barriers must be tackled and adopts a roadmap for successful implementation of DSCM and reap its benefits. Originality/value This is one of the initial research studies which has analysed the barriers of DSC using ISM approach.


2018 ◽  
Vol 8 (4) ◽  
pp. 495-510 ◽  
Author(s):  
Nidhi Sehgal ◽  
Saboohi Nasim

Purpose The purpose of this paper is to present a qualitative analysis of the significant factors that influence graduate employability in information technology (IT) sector. This is imperative, given the rising “employability gap” confronted by this sector, especially in context of India. The key factors that influence graduate employability have been drawn from the literature. This research paper aims to conduct a preliminary validation of these predictors of employability and analyse the contextual relationship between them through Total Interpretive Structural Modelling (TISM) technique (Nasim, 2011; Sushil, 2012). This technique is an innovative version of Interpretive Structural Modelling proposed by Warfield (1973). Design/methodology/approach The antecedents of graduate employability have been identified through qualitative analysis of available literature. Further, TISM has been used to derive a structural model and analyse the contextual relationship among these identified antecedents. The structural model has been derived through in-depth interviews with experts that include senior middle management professionals from reputed IT companies in India. The developed TISM model has been further validated through assessment surveys with a larger set of domain experts to enhance the credibility of the obtained results. Findings Based on the data collected from the domain experts, eight elements including employability and its seven antecedents were hierarchically modelled into four levels. While all the seven identified factors were endorsed by the industry experts as the drivers of employability, some of the key factors affecting employability emerged to be technical specialties knowledge, technology management skills and communication skills. Furthermore, the developed model has been subsequently validated and accepted based on the results of the assessment surveys conducted with a larger set of domain experts. Research limitations/implications The findings are expected to help the graduates seeking jobs in IT and allied sectors and the higher education institutions (HEIs) offering academic programmes in this domain. These findings would enable the graduates to understand the significance of the different knowledge/skill areas that influence their employability and increase the chances of securing job. Also, the HEIs can comprehend the developed model to understand the demands of the employers, the rationale behind it and further align their course curriculum/teaching methodologies in sync with their expectations. The developed model should be put to empirical validation for greater reliability. Originality/value The qualitative analysis of the antecedents of graduate employability using TISM technique is an original methodological contribution to the field. Though the TISM technique has been used in research studies across different sectors like e-government (Nasim, 2011), higher education (Prasad and Suri, 2011) and flexible manufacturing systems (Dubey and Ali, 2014), the application of this technique to employability in IT sector in India is a novel contribution.


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