Analyzing the scheduling system stage of production system life cycle

Attri, Rajesh; Grover, Sandeep

doi:10.5267/j.msl.2015.3.011

Cited by 10 publications

(5 citation statements)

References 17 publications

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“…ISM approach can be utilised by individuals as well as by the group (Diabat et al, 2014;Attri et al, 2013a, 2013b, Raj and Attri, 2011. ISM approach is an interpretive process as it utilises the group judgement for deciding the nature and direction of relationship among the identified elements of a problem (Attri et al, 2013c;Raj et al, 2012;Attri and Grover, 2015b). ISM approach has been used by a number of researcher's from its inception in numerous fields of science, engineering, technology and management.…”

Section: Ism Approachmentioning

confidence: 99%

Analysis of work-system design stage of production system life cycle using integrated ISM-MIMBI analysis

Attri

Grover

2018

IJOR

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The work-system design stage of production system life cycle (PSLC) mainly provides structure to the productivity of an organisation. It fundamentally involves the job design, worker compensation and work study. The design of work-system is not an easy task for the managers as it is affected by a number of factors hereby known as quality enabled factors (QEFs). QEFs are those factors whose consideration will lead to the better design of work-system. The ultimate need is to analyse the behaviour of these QEFs for their effective utilisation in the work-system design. The main objective of this paper is to recognise the mutual interaction of these QEFs and recognise the 'influencing QEFs' (i.e., which influence the other QEFs) and the 'influenced QEFs' (i.e., which are influenced by other QEFs). In the current work, these QEFs have been recognised through the literature analysis and expert opinions and interpretive structural modelling (ISM) approach has been utilised in analysing their mutual interaction. Afterwards, MIMBI (where MI = measure of influencing; MBI = measure of being influenced) analysis has been applied to identify the key QEFs. At last, an integrated model based on ISM and MIMBI analysis has been developed for the effective utilisation of QEFs in the work-system design.

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Section: Ism Approachmentioning

confidence: 99%

Analysis of work-system design stage of production system life cycle using integrated ISM-MIMBI analysis

Attri

Grover

2018

IJOR

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“…ISM technique has been applied in various field of supply chain such as managing size of the enterprises (Sage, 1977; Thakkar et al , 2007, Thakkar et al , 2008a, b; Dev et al , 2010), barriers in supply chain risk management and green supply chain (Thakkar et al , (2005, 2008a, b; Faisal et al , 2007; Mudgal et al , 2010; Luthra et al , 2011), third-party logistics (Thakkar et al , 2005). Managing quality of education system (Mahajan et al , 2014), product system life cycle in scheduling system (Attri and Grover, 2015a), inventory control system (Attri and Grover, 2015b), selection of vendor (Mandal and Deshmukh, 1994), healthcare sector (Meena and Thakkar, 2014), re-engineering banking services (Salimifard et al , 2010) and also understanding interrelationship of critical success factors in big data analytics projects (Sachdeva et al , 2015) have also been studied in their respective fields by ISM methodology. Overview of ISM approach has been mentioned by Attri et al .…”

Section: Literature Review: Concept Of Ism and Micmacmentioning

confidence: 99%

Interpretive structural modelling for attributes of software quality

Anand

Bansal

2017

JAMR

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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.

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“…Talib et al (2011) have analyzed the interaction among the barriers of total quality management implementation using ISM approach. Attri and Grover (2015b) have analyzed the scheduling system stage of PSLC using ISM approach. In another paper, Attri and Grover (2015c) have used this approach for establishing the contextual relationship among the QEFs of inventory control system stage of PSLC.…”

Section: Data Of Responding Organizationsmentioning

confidence: 99%

Modelling the quality enabled factors in initiation stage of production system life cycle

Attri

Grover

2017

BIJ

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Purpose The purpose of this paper is to ascertain and understand the relationship dynamics among the quality-enabled factors (QEFs) affecting the initiation stage of production system life cycle (PSLC). This study presents an approach for refining the decision making in the initiation stage of the production system. Design/methodology/approach In this paper, ten QEFs have been identified for the initiation stage of PSLC. An interpretive structural modelling (ISM) approach has been utilized to cultivate an organizational association among these identified QEFs. The results of ISM approach are used as an input to fuzzy Matriced’ Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis, to identify the driving and dependence power of QEFs. Findings The key consequences of this paper are to prioritize the strategic QEFs in reducing the risks linked with initiation stage of production system. The integrated model obtained by ISM-fuzzy MICMAC illustrates that there exists two clusters of QEFs, one is having high driving power and low dependency power which requires extreme consideration and of strategic importance (such as honesty and sincerity in collecting and analyzing field data) and other is having high dependence power and low driving power and are resultant effects (such as strategic decision-making ability). Research limitations/implications The integrated ISM-fuzzy MICMAC model developed is not statistically corroborated; consequently structural equation modelling (SEM) approach which is also known as linear structural relationship approach could be utilized to examine the validity of developed hypothetical model. Originality/value This is first study to identify ten QEFs in initiation stage of production system and further, to deploy integrated ISM-fuzzy MICMAC approach to recognize and categorize the QEFs influencing the initiation stage of production system.

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Analyzing the scheduling system stage of production system life cycle

Cited by 10 publications

References 17 publications

Analysis of work-system design stage of production system life cycle using integrated ISM-MIMBI analysis

Analysis of work-system design stage of production system life cycle using integrated ISM-MIMBI analysis

Interpretive structural modelling for attributes of software quality

Modelling the quality enabled factors in initiation stage of production system life cycle

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