Identifying Barriers of Lean Six Sigma Implementation in ...ieomsociety.org/pilsen2019/papers/390.pdfIn present day world, apparel industry is developing and exceeding surprisingly

Proceedings of the International Conference on Industrial Engineering and Operations Management

Pilsen, Czech Republic, July 23-26, 2019

© IEOM Society International

Identifying Barriers of Lean Six Sigma Implementation in

RMG Sector: A Case Study

Ferdous Sarwar, Farzana Islam, Md Sadman Sakib and Sampa Halder

Department of Industrial & Production Engineering

Bangladesh University of Engineering & Technology

Dhaka, Bangladesh

[email protected]

Abstract

In present day world, apparel industry is developing and exceeding surprisingly. To boost the productivity and quality of product or service, a method improvement tool, lean six sigma (LSS) methodology is followed in several industries. Execution of LSS technique will be far easier if the key obstructions just as their need by positioning can be discovered. To do as such, 20 barriers have been recognized by going through literature review and by taking opinions of managers who are practically connected to the organization. In this study, by applying "Interpretive structural modelling" (ISM) and "MICMAC" (Matriced' Impacts Croise´s Multiplication Applique´e a´ unClassement) strategy, a logical relationship among the barriers has been built up and those barriers have been isolated into various classes as per their reliance and driving force on one another.

Keywords: Barriers, Lean Six Sigma, Interpretive Structural Modeling, MICMAC.

1. Introduction

The Ready-made garments (RMG) industry in Bangladesh is an extraordinary prospect as it has been the greatest foreign currency earner in its history. Decisions made by its pioneers can have noteworthy effect on its changing future on account of its unparalleled development. The business stands the chance to turn into the leading export oriented RMG production center in the world through providing high caliber, fairly paid jobs and more importantly making the production process progressively productive and successful through utilizing the best possible tools and techniques to guarantee the advancement of this life saver industry of the nation since this sector has to manage both cost and compliance. To adapt to the changing dynamics of international apparel industry, continuous improvement of both forward and backward linkage is an absolute necessity to increase worldwide status.

To improve the method in successful way, extraordinary strategies are being sought after. Among them Lean manufacturing process and six sigma has increased critical prevalence. Lean manufacturing process allots an incentive to the raw material despite the fact that it lessens waste. Then again, six sigma definitely diminishes the nonconformity of finished products through effective problem solving techniques. In the ongoing years, shorter product life cycle requests shorter time to advertise which can be met by incredible usage of lean six sigma. Usage of these two techniques is making the procedure significantly simpler to finish than ordinary procedure. In lean six sigma process, process improvement is quicker and increasingly proficient on the grounds that lean accelerates six sigma process. (Cherrafi, Elfezazi, Chiarini, Mokhlis, & Benhida, 2016). To ensure customer satisfaction, this process sets its focus on defect prevention instead of defect prevention to ensure the proper use of resources through creating work standard and adjusted stream. The barriers of lean six sigma debilitates the proficiency of organization’s procedures. Also, there are between relationships among the barriers which have not yet been analyzed.

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Therefore, this paper centers around determining the inter-relationship among different barriers of lean six sigma which are impairing the process using Interpretive Structural Modeling (ISM) framework and MICMAC (Matriced’ Impacts Croise´s Multiplication Applique´e a´ unClassement) analysis to establish a contextual relationship among the 20 selected barriers and to classify the barriers according to their impact on industry's overall performance. 2. Literature Review

Coordination of lean and six sigma expects to beat the inadequacies of both. The combination of the two nonstop improvement strategies is a route for associations to build their potential improvement. Both Six Sigma and Lean management have advanced into far reaching the board frameworks. For each situation, their compelling usage includes social changes in associations, new ways to deal with creation and adjusting customers and a high level of preparing and training of employees, from upper administration to the line laborer (Arnheiter & Maleyeff, 2005). Pamfilie et al. (2012) concentrated on recognizing the key components for an effective Lean Six Sigma the executives related the progressions which happen inside the association in their study (Pamfilie, & Draghici, 2012). After numerous perplexity about whether to actualize Lean management procedure or six sigma process, Assarlind et al. (2014) deduced in their exploration that there has been noteworthy interest for the joining of lean and six sigma (Assarlind, Aaboen, & Assarlind, 2014).

There are numerous obstructions that may impact fruitful reception of lean six sigma (LSS) execution. Antony et al. (2014) identified 12 barriers to implement LSS (Antony, Krishan, Cullen, & Kumar, 2014). Jadhav et al. (2014) found discoveries got from the assessment of the distributions investigation have prompted the recognizable proof of 24 lean hindrances (Jadhav, Mantha, & Rane, 2014). Snee (2010) found basic issues incorporate utilizing LSS to create cash in troublesome monetary occasions, advancement of information based procedure the executives frameworks and the utilization of taking a shot at progress as an initiative improvement apparatus (Snee, 2010). He additionally presumed that the improvement of the procedure must address the progression of data and materials intensive procedures just as the upgrade of significant worth including process steps that make the item for the customer. Kumar et al. (2016) experienced 494 papers and distinguished 21 barriers which function as check in the execution of the green LSS procedure (Kumar, Luthra, Govindan, & Kumar, 2016). They found that 'Absence of Real Support of Management' plays as the most noteworthy obstruction in green lean six sigma usage in the automotive industry (Kumar et al., 2016). Many industries nowadays trying to implement this procedure. Albliwi et al. (2014) expressed that there are some basic failures while actualizing LSS methodology, for example, absence of top administration duty and inclusion, absence of correspondence, absence of preparing and instruction, restricted assets and others (Albliwi, Sarina, Halim, & Wiele, 2014). Be that as it may, none of the researcher doled out significance factors to the chose obstructions of LSS while executing the procedure in RMG sector.

3. Methodology:

To recognize the potent barriers of implementing LSS in RMG sector, numerous online surveys were conducted among IE experts, academic experts & expert executives of RMG sector along with current literature reviews. After identifying the puissant barriers with the assistance of expert opinion and literature reviews, ISM technique was used to develop framework. The MICMAC analysis was applied to illustrate the hierarchical relationship among these barriers associated with the implementation of LSS. With the knowledge of interrelation among these puissant barriers, effectual implementation of LSS in RMG sector may be possible.

3.1. Interpretive Structural Modelling (ISM)

Interpretive Structural Modelling is an intuitive learning process (Tiwari, 2013). Sometimes it becomes very tough to understand a system when there are many interrelated elements present in the framework. At times it turns out to be hard to comprehend a framework when there are many interrelated components present in the system. Presence of direct and indirect cooperation among these components increase the multifaceted nature of any procedure (Sarwar et al. 2019). This zero-information added powerful systematic model transform unclear & poorly articulated models of system into visible & well-defined models (Tiwari, 2013). The various steps involved in ISM technique are- Step 1: Identification of the potent barriers in implementing LSS in RMG sector with the assistance of expert opinions & literature reviews.

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Step 2: A contextual relationship was established among the identified barriers (in Step 1), with the pairs of examined barriers. Numerous online surveys were directed to find the contextual relationship (T, Radhika, & Pramod, 2014). Step 3: A structural self-interaction matrix (SSIM) was created. It expresses the pair-wise association between the barriers. With the assistance of existing contextual interaction between two barriers (i & j), the related direction of relationship was questioned (Attri, Dev, & Sharma, 2013). Four images were utilized to recognize the course of connection between two elements (i & j). (a) V for the connection from factor i to factor j (i.e., factor i will impact factor j) (b) A for the connection from factor j to factor i (i.e., factor i will be affected by factor j) (c) X for both bearing relations (d) O implies no connection between the components (i.e., barriers i and j are not related). Step 4: A reachability matrix was established using the SSIM & and incorporating transitivity where needed. An essential feature in ISM is ransitivity which expresses that if P is identified with Q and Q is identified with R, at that point P will be fundamentally identified with R. To establish the reachability matrix 0 and 1 were used for replacing the notations of SSIM (V, A, X, O). To replace this notations, the conditions followed are: (a) 1 was placed for (i, j) and 0 was used for (j, i) when V was placed in SSIM for (i, j). (b) 0 was placed for (i, j) and 1 was placed for (j, i) when A was used in SSIM for (i, j). (c) 1 was used for both (i, j) and (j, i) when X was used in SSIM for (i, j). (d) 0 was used for both (i, j) and (j, i) when O was Placed in SSIM for (i, j) (Attri et al., 2013). Step 5: The reachability and predecessor set for each barrier were found from the last reachability network. By then the union of the sets was progressed for all barriers. The best one is implied in the ISM chain of command when the part for the reachability and union sets were same. At the point when the top-level barrier was found, it was expelled from substitute barriers. With a similar framework, the accompanying level of barriers were found. For making the diagraph and last model, the indicated dimensions were utilized. This cycle was reiterated till the level of every barrier are chosen. Step 6: With the help of clustering in a comparative level of rows and columns of the final reachability matrix, a conical matrix was derived (Tiwari, 2013). Drive power and dependence are two significant key components of this matrix. The drive power of a factor was figured by including the amount of 1s in the rows and dependence by including the amount of 1s in the columns. The positioning course of action of these drive power and dependence was processed with the amount of 1s in the rows and columns independently. Step 7: Digraph of the barriers for actualizing LSS speaks to the relationship between the barriers. From the final reachability matrix, the methodical model was made by strategies for vertices or center points and lines of edges. The bolt which shows from i to j exhibits the association between the barrier i and j. As direction is exhibited in this diagram so it is known as directed graph or digraph (Tiwari, 2013). Step 8: The ISM model was developed from this digraph by replacing node with statement (Attri et al., 2013). 3.2. MICMAC Analysis The expansion of MICMAC is Matrice d’Impacts croises-multiplication appliqúe an classment (cross-impact matrix multiplication applied to classification)(Attri et al., 2013). Analyzing drive power and dependence power is the primary objective of MICMAC analysis. Multiplication property of matrix is the basic foundation of MICMAC principal. With the assistance of drive power and dependence power the barriers are divided into four clusters.

Autonomous barriers: Weak drive and weak dependence power are the criteria for autonomous barriers. This type of barriers is generally separated from the framework. These barriers have least power to influence other barriers of the system.

Linkage barriers: Strong drive power and strong dependence power are the criteria for linkage barriers. These barriers are known as unstable barriers (Attri et al., 2013).

Dependent barriers: Weak drive power but strong dependence power are the criteria for dependent barriers.

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Independent barriers: Strong drive power but weak dependence power are the criteria for independent barriers.

Which barrier has strong drive power is known as key barrier. Based on this criteria linkage barrier and independent barrier are key barriers. 4. Case Study

4.1 Application of Interpretive Structural Modeling(ISM) Method

The developed ISM methodology has been used to rank the barriers of the Lean six sigma implementation and this has been followed by a hierarchy of these barriers. Among all the potential barriers, twenty has been shortlisted though expert opinion. This survey has been done on the experts who are closely related to RMG sector. ISM methodology has been applied to this case study to find out the interrelationship between the barriers and to provide a multi-objective decision model using ISM based approach which can successfully initiate Lean Six Sigma in RMG sector.

4.2 Interpretive Structural Model Development

Contextual relation between the barriers of LSS

Many barriers of lean six sigma implementation in different types of industries have been identified and through literature review and expert feedback, only twenty of them has been selected. These barriers are interrelated and influence each other in an effective manner which encouraged to develop the contextual relationship between the selected barriers.

Table 4.1: Identification code of the barriers of lean six sigma

Identification code Barrier of Lean Six Sigma EB1 Lack of top management support

EB2 Poor involvement of employees EB3 Absence of strong leadership EB4 Poor communication system EB5 Lack of knowledge and awareness EB6 Lack of competence of mid-level manager EB7 Low efficient tool which does not add sufficient value EB8 Different function and hierarchical level EB9 Absence of reward and recognition for doing a better job

EB10 Problems with machines and plant configuration EB11 Absence of customer and supplier involvement EB12 Worker's reluctant behavior EB13 Absence of employee empowerment EB14 Lack of funds for lean six sigma practices EB15 Workers' resistance to change and adopt new practice EB16 Lack of logistic supports EB17 Lack of formal training for managers about the process EB18 Project manager's lack of adequate skill about project management EB19 Lack of formal training for workers about the process EB20 Subcontractor's compromised quality of work

Developing Structural Self-Interaction Matrix (SSIM)

Through expert opinion taken on a survey sheet which contained the barriers of LSS implementation, the contextual relationship of the barriers of LSS has been marked in four different criteria. This four criteria are denoted through four different standard symbols, which also define the direction of the relationship between variables (Singh, Garg, & Deshmukh, 2007).

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Table 4.2: Structural Self-Interaction Matrix

EB1 EB2 EB3 EB4 EB5 EB6 EB7 EB8 EB9 EB10 EB11 EB12 EB13 EB14 EB15 EB16 EB17 EB18 EB19 EB20

EB1 X V O V A V V O V O O V V V O V V O V V EB2 X X A A A O V A O O V A A A O A A A O EB3 X V A A O A A O O V V O V O A A O O EB4 X A A O A O O V V A V V V A A A V EB5 X V V A A V V V O X V V A A A O EB6 X V A A V V V V A O V A O O V EB7 X O O V X O A A O V X O A V EB8 X O V O V V V O X O O V V EB9 X O V V O O V V O O O V

EB10 X O V A A O V A A A V EB11 X O O O O X A A O V EB12 X A A A O A A X O EB13 X A O O A A A O EB14 X V V V V V V EB15 X O A A A O EB16 X O O O V EB17 X V V V EB18 X V V EB19 X O EB20 X

Developing the initial and final reachability matrix

The SSIM developed is converted into a binary matrix by substituting the letters used (V, A, O, X) with only 1 and 0 per case. This substitution is done maintaining the conditions and the outcome has been show below.

Table 4.3: Initial Reachability Matrix

EB1 EB2 EB3 EB4 EB5 EB6 EB7 EB8 EB9 EB10 EB11 EB12 EB13 EB14 EB15 EB16 EB17 EB18 EB19 EB20

EB1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 0 1 1 EB2 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 EB3 0 1 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 EB4 0 1 0 1 0 0 0 0 0 0 1 1 0 1 1 1 0 0 0 1 EB5 1 1 1 1 1 1 1 0 0 1 1 1 0 1 1 1 0 0 0 0 EB6 0 1 1 1 0 1 1 0 0 1 1 1 1 0 0 1 0 0 0 1 EB7 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 1 0 0 1 EB8 0 0 1 1 1 1 0 1 0 1 0 1 1 1 0 1 0 0 1 1 EB9 0 1 1 0 1 1 0 0 1 0 1 1 0 0 1 1 0 0 0 1

EB10 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 EB11 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 EB12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 EB13 0 1 0 1 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 EB14 0 1 0 0 1 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 EB15 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 EB16 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1

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EB17 0 1 1 1 1 1 1 0 0 1 1 1 1 0 1 0 1 1 1 1 EB18 0 1 1 1 1 0 0 0 0 1 1 1 1 0 1 0 0 1 1 1 EB19 0 1 0 1 1 0 1 0 0 1 0 1 1 0 1 0 0 0 1 0 EB20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

In next table, driving power and dependence have been denoted by D1 and D2 respectively.

Table 4.4: Final Reachability Matrix

EB1 EB2 EB3 EB4 EB5 EB6 EB7 EB8 EB9 EB10 EB11 EB12 EB13 EB14 EB15 EB16 EB17 EB18 EB19 EB20 D1

EB1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 0 1 1 17 EB2 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 EB3 0 1 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 6 EB4 0 1 0 1 0 0 0 0 0 0 1 1 0 0 1 1 0 0 0 1 7 EB5 1 1 1 1 1 1 1 0 0 1 1 1 0 1 1 1 0 0 0 0 13 EB6 0 1 1 1 0 1 1 0 0 1 1 1 1 0 0 1 0 0 0 1 11 EB7 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 1 0 0 1 6 EB8 0 0 1 1 1 1 0 1 0 1 0 1 1 1 0 1 0 0 1 1 12 EB9 0 1 1 0 1 1 0 0 1 0 1 1 0 0 1 1 0 0 0 1 10

EB10 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 4 EB11 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 4 EB12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 2 EB13 0 1 0 1 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 6 EB14 0 1 0 0 1 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 14 EB15 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 3 EB16 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 4 EB17 0 1 1 1 1 1 1 0 0 1 1 1 1 0 1 0 1 1 1 1 15 EB18 0 1 1 1 1 0 0 0 0 1 1 1 1 0 1 0 0 1 1 1 12 EB19 0 1 0 1 1 0 1 0 0 1 0 1 1 0 1 0 0 0 1 0 9 EB20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1

D2 2 13 9 10 8 7 9 3 2 11 9 16 9 4 9 11 4 3 7 13 159

Level Partitioning of the Final Reachability Matrix

For dividing the barriers into different sets, reachability and antecedent set is identified first. To get the reachability matrix, every column that contains 1 in the row of the considered barrier is grouped together as reachability matrix. Again, to get the antecedent set, every row that contains 1 in the column of considered barrier is grouped together. The intersection of these two set is named as intersection set. When the intersection set is equal to the reachability set, that barrier is marked with a level and excluded from the further iterations.

Table 4.5: Level partition Iteration 1

Barriers Reachability Set Antecedent Set Intersection Set Level EB1 EB1, EB2, EB3, EB4, EB5,

EB6, EB7, EB8, EB9, EB10, EB12, EB13, EB14, EB16, EB17, EB19, EB20

EB1, EB5 EB1, EB5

EB2 EB2, EB3, EB12 EB1, EB2, EB3, EB4, EB5, EB6, EB9, EB13, EB14, EB15, EB17, EB18, EB19

EB2, EB3

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EB3 EB2, EB3, EB4, EB12, EB13, EB15

EB1, EB2, EB3, EB5, EB6, EB8, EB9, EB17, EB18

EB2, EB3

EB4 EB2, EB4, EB11, EB12, EB15, EB16, EB20

EB1, EB3, EB4, EB5, EB6, EB8, EB13, EB17, EB18, EB19

EB4

EB5 EB1, EB2, EB3, EB4, EB5, EB6, EB7, EB10, EB11, EB12, EB14, EB15, EB16,

EB1, EB5, EB8, EB9, EB14, EB17, EB18, EB19

EB1, EB5, EB14

EB6 EB2, EB3, EB4, EB6, EB7, EB10, EB11, EB12, EB13, EB16, EB20

EB1, EB5, EB6, EB8, EB9, EB14, EB17

EB6

EB7 EB7, EB10, EB11, EB16, EB17, EB20


EB7, EB11, EB17

EB8 EB3, EB4, EB5, EB6, EB8, EB10, EB12, EB13, EB14, EB16, EB19, EB20

EB1, EB8, EB16 EB8, EB16

EB9 EB2, EB3, EB5, EB6, EB9, EB11, EB12, EB15, EB16, EB20

EB1, EB9 EB9

EB10 EB10, EB12, EB16, EB20 EB1, EB5, EB6, EB7, EB8, EB10, EB13, EB14, EB17, EB18, EB19

EB10

EB11 EB7, EB11, EB16, EB20 EB4, EB5, EB6, EB7, EB9, EB11, EB16, EB17, EB18

EEB7, EB11, EB16

EB12 EB12, EB19 EB1, EB2, EB3, EB4, EB5, EB6, EB8, EB9, EB10, EB12, EB13, EB14, EB15, EB17, EB18, EB19

EB12, EB19 I

EB13 EB2, EB4, EB7, EB10, EB12, EB13


EB13

EB14 EB2, EB5, EB6, EB7, EB10, EB12, EB13, EB14, EB15, EB16, EB17, EB18, EB19, EB20

EB1, EB5, EB8, EB14 EB5, EB14

EB15 EB2, EB12, EB15 EB3, EB4, EB5, EB9, EB14, EB15, EB17, EB18, EB19

EB15

EB16 EB8, EB11, EB16, EB20 EB1, EB4, EB5, EB6, EB7, EB8, EB9, EB10, EB11, EB14, EB16

EB8, EB11, EB16

EB17 EB2, EB3, EB4, EB5, EB6, EB7, EB10, EB11, EB12, EB13, EB15, EB17, EB18, EB19, EB20

EB1, EB7, EB14, EB17 EB7, EB17

EB18 EB2, EB3, EB4, EB5, EB10, EB11, EB12, EB13, EB15, EB18, EB19, EB20

EB14, EB17, EB18 EB18

EB19 EB2, EB4, EB5, EB7, EB10, EB12, EB13, EB15, EB19

EB1, EB8, EB12, EB14, EB17, EB18, EB19

EB12, EB19

EB20 EB20 EB1, EB4, EB6, EB7, EB8, EB9, EB10, EB11, EB14, EB16, EB17, EB18, EB20

EB20 I

Following the process stated above, all the barriers has been divided into 11 levels which is summarized below through the final list of level partitions.

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Table 4.6: Final list of Level Partition

Level Barriers No Barriers I EB12 Worker's reluctant behavior EB20 Subcontractor's compromised quality of work

II EB2 Poor involvement of employees EB11 Absence of customer and supplier involvement

III

EB16 Lack of logistic supports EB15 Workers' resistance to change and adopt new practice EB10 Problems with machines and plant configuration

IV V

EB4 Poor communication system EB7 Low efficient tool which does not add sufficient value

EB13 Absence of employee empowerment VI VII

EB3 Absence of strong leadership EB6 Lack of competence of mid-level manager

VIII IX

EB5 Lack of knowledge and awareness EB9 Absence of reward and recognition for doing a better job

EB19 Lack of formal training for workers about the process X XI

EB18 Project manager's lack of adequate skill about project management EB17 Lack of formal training for managers about the process

XII XIII

EB14 Lack of funds for lean six sigma practices EB8 Different function and hierarchical level

XIV EB1 Lack of top management support

Final Diagraph

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Figure 4.1: Final Diagraph of LSS Barriers

4.3 Proposed ISM Model

Figure 4.2: Proposed ISM Model for Barriers

5. Results Obtained from Micmac Analysis

Figure 4.3: MICMAC Analysis of LSS Barriers

The purpose of MICMAC analysis is further analysis of the barriers of LSS. It is done by putting dependence and driver power in X and Y axis respectively. Here cluster I represents “autonomous barrier”. Among 20 barriers, 12

1

2

34

56

7

89

1011

12

13

14

15

16

17

18

19

2002468

101214161820

0 5 10 15 20

Driv

er P

ower

Dependence

Cluster II

Cluster IV Cluster III

Cluster I

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barriers have been found in this cluster. These selected autonomous factor for LSS are: EB3, EB7, EB11, EB13, EB15 and EB19. Cluster II represents “dependent barrier”. Manager should take special care of these barriers for successful implementation. Four barriers have been found as dependent factors. These are EB2, EB4, EB10, EB12, EB16 and EB20.

Cluster III represents “linkage barrier” which is highly unstable. Any action on this factor can imply effects on others, also there will be feedback on themselves. Among our selected barriers none has showed this unstable nature.

Lastly, cluster IV represents “independent barrier”. This factor is called key factor as it plays vital role for the implementation of the system. Here we have found EB1, EB5, EB6, EB8, EB9, EB14, EB17 and EB18 as independent factors.

6. Result Analysis

From the ISM diagraph, we have observed that among our 20 selected barriers, lack of top management support (EB 1) plays the most vital role as it drives 16 other barriers and is dependent on only 1 barrier which means it has high driver power and low dependence. Other barriers such as different function, hierarchical level (EB 8), lack of funds for lean six sigma practices (EB 14), lack of formal training for managers about the process (EB 17), project manager's lack of adequate skill about project management (EB 18), lack of knowledge and awareness (EB 5) and Lack of competence of mid-level manager (EB 6) are also in the lower part of the hierarchy having high driving power and comparatively low dependence on other factors. They fall into cluster IV of the MICMAC analysis graph and so they are named as independent factors or barriers and they are less dependent on other factors and at the same time, capable of influencing large amount of other factors. On the other hand, worker's reluctant behaviour (EB 12) and subcontractor's compromised quality of work (EB 20) are at the top of the hierarchy and are driven by many other barriers. So these two barriers have very high dependence as they are driven by other 15 and 13 barriers respectively. And they have very low driver power as EB 12 influence only 1 other barrier and EB 20 drive no other barrier except itself. So, they fall into cluster II and these factors are recognized as dependent factors. In the middle we observe both the barriers with high driving power with high dependence and low driving power with high dependence which are named as linkage factors (cluster III) and autonomous factors (cluster II) respectively. Absence of employee empowerment (EB 13), workers' resistance to change and adopt new practice (EB 15) and lack of formal training for workers (EB 19) are some examples of autonomous factors. No factors from the selected barriers fell into the cluster of linkage factors which shows unstable characteristics.

7. Conclusion

Interpretive Structural Modeling (ISM) causes us to build up a precise and directional structure for a complex framework alongside a practical image of the framework. It shows both direct and indirect relationship among the basic barriers of debilitating LSS in RMG sector. It additionally gives distinctive dimensions of the intense barriers. With the assistance of these dimensions of the barriers, a basic structure is created. With the assistance of these structure and information of various dimensions of various barriers, a manager can co-ordinate among these barriers without much of a stretch which will quicken the way toward actualizing LSS in RMG division. MICMAC analysis gives four distinctive group through driving power and dependence. From this ISM model and MICMAC examination we locate the basic barriers and interrelationship among them which will impede the way toward actualizing LSS in RMG sector.

Acknowledgements

This research has been done under fully cooperation and resources of Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology (BUET). The authors express gratitude for all the efforts and cooperation to complete the research.

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Biographies Ferdous Sarwar received his B.Sc. (summa cum laude) and M.Sc. in Industrial & Production Engineering (IPE) from BUET and Ph.D. in Industrial & Manufacturing Engineering (IME) from North Dakota State University (NDSU), USA. He is an Associate Professor of Industrial and Production Engineering with BUET. His research interest includes optimization and supply chain management. He is a Member of the International Microelectronics and Packaging Society (IMAPS), the Surface Mount Technology Association (SMTA), and the Institute of Industrial Engineers (IIE).

Farzana Islam is a final year student in the Department of Industrial & Production Engineering (IPE), BUET. Her research interest is Modeling and Simulation, Operations Research, Process Engineering

Md Sadman Sakib is a final year student in the Department of Industrial & Production Engineering (IPE), BUET. His research interest is Modeling and Simulation, Supply Chain Analysis, Operation Research.

Sampa Halder is a final year student in the Department of Industrial & Production Engineering (IPE), BUET. His research interest is Modeling and Simulation, Supply Chain Analysis, Operation Research.

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https://doi.org/10.1108/IJQRM-09-2013-0147https://doi.org/10.1108/17410401211277165https://doi.org/10.1108/09544780510573020https://doi.org/10.1108/IJLSS-07-2013-0039https://doi.org/10.1080/09537287.2016.1165307https://doi.org/10.1016/j.sbspro.2012.09.992https://doi.org/10.1108/20401461011033130

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