An approach for evaluation of process sustainability using multi-grade fuzzy method

Abstract

The rapidly changing modern marketplace and government policies drive an organization to endeavour sustainable manufacturing. Sustainable manufacturing means the production of products/services in such a way that it utilizes minimum natural resources and produces safer, cleaner and environment-friendly products at an affordable cost. Sustainable development in a manufacturing firm can be achieved using three orientations such as material, product design and manufacturing process. Among the three perspectives, process perspective gains more importance because it directly contributes to emissions, energy and resource consumption. Hence, the process sustainability index (PSI) needs to be quantified. In this study, a comprehensive model for assessing process sustainability has been developed. Then by using multi-grade fuzzy approach, PSI has been quantified as 6.94 and performance importance index was computed which helps in identifying the obstacles to enable sustainability improvement. The results indicate that the developed conceptual model is capable of effectively assessing sustainability of process orientation and has practical relevance.

Keywords::

• sustainable development
• sustainability
• process sustainability
• multi-grade fuzzy approach
• conceptual model
• drag factors

Notations

R	=	Performance rating obtained from expert team
	=	Weights obtained from expert team
	=	Performance rating for kth attribute obtained from nth expert
	=	Single factor vector obtained from expert team
	=	Process sustainability single factor vector
	=	Performance importance index for jth criteria in ith enabler
	=	Complement of performance index of kth attribute given by nth expert

1. Introduction

The rising global environmental problems due to over consumption of natural resources and pollution result in enforcement of strong government regulations applied to both manufacturers and product users. Due to stringent conditions prevailing in the markets, manufacturers are ready to follow these conditions to maintain a good position in the market. In order to stay competitive in the dynamic market scenario and also to meet new regulations, many organizations started adopting sustainable manufacturing. Sustainable manufacturing is the subset of the broad topic of sustainable development. Sustainability is recognized as an important concept for survival in the competitive business environment (Bevilacqua, Ciarapica, and Giacchetta 2007). Ljungberg (2007) identified four vital problems such as over-consumption, resource utilization, pollution and over-population as reasons for unsustainability at global level, and while developing any new product, it is necessary to move between three E's (ecology, equity and economy) in order to obtain sustainable development. These three E's are often referred as triple bottom line (TBL) namely environment, economy and society which are identified as the core pillars of sustainability. They are alternatively referred to as profitability, people and planet. Few researchers have contributed towards sustainability improvement through studies on TBL. In recent times societal and economic dimensions are also considered equal to environment (Vince et al. 2008; Foolmaun and Ramjeawon 2008; Middleton 2013).

Sustainability assessment is being increasingly viewed as an important tool to aid in the shift towards sustainability (Singh et al. 2012; Nzila et al. 2012; Vinodh et al. 2014). The aim of sustainability assessment is to ensure that ‘plans and activities make an optimal contribution to sustainable development’ (Verheem and Tonk 2000).

The TBL concept proposed by Elkington (1997) is the basic concept used to measure sustainability in three orientations. From the literature review, it was found that many studies have been conducted on material orientation (Ljungberg 2007; Giudice 2005; Weaver 1996; Jeya Girubha and Vinodh 2012; Laurent, Olsen, and Hauschild 2010; Ingarao et al. 2012; Lindahl et al. 2014) and product orientations of sustainability (Ljungberg 2007; Vinodh and Rathod 2010; Maxwell and Van der Vorst 2003; Howarth and Hadfield 2006; Kaebernick, Kara, and Sun 2003; Bovea and Pérez-Belis 2012; Mayyas et al. 2012). Unlike leanness assessment (Smolak and Murnen 2008; Vinodh and Chintha 2011; Wan and Frank Chen 2008; Vinodh and Vimal 2012) and agility assessment (Vinodh and Devadasan 2011; Lin, Chiu, and Chu 2006, Lin, Chiu, and Tseng 2006; Yang and Li 2002), and even in general sustainability assessment (Gibson et al. 2005; Singh et al. 2009), no concrete research has been reported to the best knowledge of the authors on process sustainability (PS) assessment. Also these above-mentioned studies justified the practical relevance with improvement proposals.

In recent times among three sustainability orientations (material, product and process), process perspective gains more importance as it directly contributes to emissions, energy and resource consumption. But very few studies have been conducted in the orientation of PS (Jayal et al. 2010; Ku-Pineda and Tan 2006) and material orientation (Jeya Girubha and Vinodh 2012) and no evident studies have been reported on the assessment of PS. Labuschagne, Brent, and Van Erck (2005) highlighted the lack of existing model in assessing the sustainability in three orientations.

There exists a need for the development of a comprehensive model for assessment of PS in the context of manufacturing process in order to emphasize environmental friendliness, human health, energy conservation, etc. PS assessment helps the management to understand current PS characteristics prevailing in the organizations and also provides an opportunity for identifying the potential areas for improvement. Also, this study claims to have practical relevance towards improvement. This necessitates the development of an exclusive model to assess the PS which is also the need of the hour. Also, the organization had aspiration to assess their PS level using a scientific model. These gaps force us to formulate the research objectives as follows.

• To develop a comprehensive framework to assess PS encompassed with environmental, economic and social indicators.

• To reduce vagueness and uncertainty associated with assessment methodology.

• To develop indices for PS and to explore practical usability.

In order to fulfill the above-mentioned research objectives, a comprehensive model for process sustainability has been developed.

The uniqueness of the study is that it attempts to develop a comprehensive model to assess sustainability from a process perspective and to apply subjective evaluation for the assessment of PS which overcomes the drawbacks associated with conventional crisp approaches. This was claimed as the generic model with the literature support for assessing the PS level of the organization. The developed model has practical relevance which is being proved with the literature review. The multi-grade fuzzy (MGF) approach was proved to be a suitable technique to handle vague and uncertain environment in the performance assessment of manufacturing systems (Yang and Li 2002; Vinodh 2010; Vinodh and Chintha 2011). Also, the MGF method is very simple to understand and from industrial practitioners’ perspective, MGF was found to be a user friendly approach.

The outcome of the assessment method indicates the status of an organization from the perspectives of environmental management, pollution prevention and control aspects, waste management, energy conservation, environmental friendliness, end-of-life disposal, resource usage, implication of health hazards and its practices, etc. Besides assessing PS, associated drag factors and areas of improvement have been derived. The developed conceptual model has been validated by conducting a study in the case organization.

The paper is organized into six sections. In Section 1, the basic definition of sustainability, orientations of sustainability, studies conducted on material and product orientations are summarized. In Section 2, the methodology followed during the conduct of the case study is described. In Section 3, the conceptual model is developed. In Section 4 the case study is reported. In Section 5, the results derived by conducting the case study and practical implications are discussed. In Section 6, conclusions and future directions are presented.

2. Methodology

The methodology followed during this study is shown in Figure 1. As shown, this study has four stages namely: conceptual model development, conduct of case study, PS evaluation and gap analysis. In Stage 1, the conceptual model development starts with literature review. The research gap favours the study of PS assessment. Based on the literature review, a conceptual model has been developed, which is divided into three levels namely enabler, criterion and attribute. The term ‘enabler’ in the model means the core dimensions of PS; criterion means various subcategories and attribute forms the core element of the individual indicator. The results of earlier studies notably Vinodh and Devadasan (2011) and Lin, Chiu, and Tseng (2006) motivated us to develop a three-level model because this kind of architecture generates effective results as claimed by the authors. In Stage 2, a case organization has been identified for the conduct of the study. Then an expert team of five members has been formed. Experts were asked to assess the criterion, enabler and attribute using weights and attributes (Yang and Li 2002). The product of weights and attributes was a single factor assessment vector which is a two-dimensional array represented in a matrix form.

Figure 1 Methodology.

In Stage 3, process sustainability index (PSI) was determined and it is then matched with linguistic terms. Most PS measurements are described subjectively by linguistic terms, which are characterized as vague and uncertain. In this context, the MGF approach has been used for evaluating PS in the case organization. The reasons for selecting fuzzy concept to assess PS levels were as follows: it is imprecise, vague bounded with uncertainty. Saaty (1988) proposed the idea of using linguistic terms during assessment where subjectivity occurs. Yang and Li (2002) proposed and used the MGF evaluation methodology also called as single factor assessment vector determination for assessing the agile performance of an organization. The basic requirement for MGF is the framework which needs to be linked in hierarchical form. This model was found to be appropriate for PS assessment.

Finally in Stage 4, drag factors which form obstacles for improvement were identified. Then improvement proposals for the elimination of obstacles were identified.

3. Conceptual model

The conceptual model developed to assess PS is shown in Tables 123. The model is comprehensive for PS assessment as it focuses on the TBL. Elkington (1997) proposed TBL as the basic concept for assessment of material, product and process orientations.

Table 1 Conceptual model – economic sustainability enabler.

Enabler	Criteria	Attribute	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
Economic sustainability	Flexibility and response to changes	Production flexibility	^*
		Market flexibility																				^*
		Retrofitting of machine tools		^*
	Operating controls	Development of SOP						^*
		Monitoring and observation of equipment performance									^*
		Operation controls activated through in-line monitoring							^*
	Reciprocal arrangements	Two organizations to back each other up													^*
		Organization to use each other's resources												^*
		Rendering assistance to each other													^*
	Conflict resolution	With suppliers					^*
		In workplace														^*
		With customers														^*
	JIT capability	Pull system			^*
		Lead time								^*
		Building core competence																		^*
	Maintainability	Analysis of repetitive equipment failure																	^*
		Evaluation of maintenance cost and alternatives											^*
		Formation of new strategies to prevent failure				^*
	Defect ratio	Proper inspection plan
		Quality improvement programme																			^*
		Professional techniques																			^*
	Testing methods	Availability of testing equipment																	^*
		SOP for testing						^*
		Efforts to improve testing efficiency
	Reverse logistics	Uncertainty in material recovering
		Reverse logistics network															^*
		Stochastic routing problem																^*
	Value stream management	Adaptation of value stream mapping										^*
		Elimination of deadly wastes			^*
		Adaptation of processes for better vendor–supplier relationship		^*

Notes: 1. Guneri, Ertay, and Yucel (2011); 2. Vinodh and Vimal (2012); 3. Vinodh and Chintha (2011); 4. Vinodh, Kumar, and Vimal (2014); 5. Uzzi (1997); 6. Gross, Treu, and Unger (2001); 7. Mehra, Kilduff, and Brass (2001); 8. Lokesh and Jain (2010); 9. Aydın Keskin, Ilhan, and Ozkan (2010); 10. Johnson (1998); 11. Ha and Krishnan (2008); 12. Gulati and Gargiulo (1999); 13. Gulati (1998); 14. Golfetto and Gibbert (2006); 15. Fleischmann (2003); 16. Dethloff (2001); 17. Dalalah, Hayajneh, and Batieha (2011); 18. Baron and Markman (2003); 19. Anand and Khanna (2000); 20. Agarwal, Shankar, and Tiwari (2006); SOP, standard operating procedure.

Table 2 Conceptual model – environmental sustainability.

Enabler	Criteria	Attributes	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21
Environmental Sustainability	Management for hazardous substances	Safety handling, use and transportation of materials												^*
		Action towards hazardous material substance minimization												^*
		Hazardous waste disposal												^*
	Recyclability	Facilities available										^*
		Collecting consumer wastes			^*
		Recyclability of materials used		^*
	Re-manufacturing, re-usability, re-design	Ability to balance with the demand													^*
		Disassemblability of used product															^*
		Reconditionability and re-assemblability													^*
	Environmental management	Technological awareness which help in decision-making																		^*
		Formulation of in-house technologies and principles											^*
		Usage of scientific tools/techniques to optimize environmental resource consumption								^*
	Pollution prevention and control aspects	Release of water effluents and pollutants																			^*
		Water usage																			^*
		Release of liquid effluents									^*
	Carbon footprint	Eutrophication																				^*
		Acidification																				^*
		Energy consumption														^*
	Waste management	Waste collection mechanism																			^*
		Segregation of wastes into degradable and non-degradable																			^*
		Appropriate methodology for waste processing																			^*
	Energy conservation	Conduct of energy audit														^*
		Exploring the scope for renewable energy usage														^*
		Effective training for energy conservation										^*
	Environmental friendliness	Usage of eco-friendly materials									^*
		Development of cleaner technologies.																					^*
		Design to improve eco-friendly nature of product (design for environment)					^*
	EoL disposal	Clean development mechanism practice					^*
		Carbon foot-print																^*
		Land fill	^*
	Resource usage	Land use	^*
		Consumption of minerals and rare earth elements						^*
		Consumption of fossil fuels																				^*
	Green image	Contribution to society				^*
		Innovative forward looking							^*
		Green marketing																	^*

Notes: 1. Becker (1997); 2. Noci (1997); 3. Mebratu (1998); 4. Bai and Sarkis (2010); 5. Satff (1993); 6. Cui, Wang, and Hu (2008); 7. Dalalah, Hayajneh, and Batieha (2011); 8. Emek and Kara (2007); 9. Jeya Girubha and Vinodh (2012); 10. Guneri, Ertay, and Yucel (2011); 11. Hall (2000); 12. Hsu et al. (2013); 13. Hussain (2011); 14. Boustead (1979); 15. Jovane et al. (1993); 16. Laurent, Olsen, and Hauschild (2010); 17. Lee et al. (2009); 18. Robins (2006); 19. Silva et al. (2007); 20. Vinodh, Jayakrishna, and Joy (2012); 21. Moors, Mulder, and Vergragt (2005); EOL, end of life.

Table 3 Conceptual model – social sustainability.

Enabler	Criteria	Attributes	1	2	3	4	5	6	7	8	9	10	11	12	13
Social Sustainability	Employee compensation practices	Contribution-based remuneration								^*
		Reward valued behaviour								^*
		Ensure equity and motivate to retain staff						^*
	Enforcement for socio-environmental performance	Culture for socio-economic performance				^*
		Compliance to government regulations							^*
		Conduct of awareness programmes			^*
	Implication of health hazards and its practices	Usage of personal protection equipment										^*
		Toxicity of product and time of exposure of product if inhaled												^*
		Magnitude and time of exposure to noise												^*
	Employee career development programme (Employee Training and orientation)	Human rights						^*
		Training season in advance manufacturing process and evaluation for continuous improvement					^*
		Evaluation for continuous improvement													^*
	Employee involvement	Employee recognition through appraisal schemes						^*
		Involvement of employee in group decision-making											^*
		Strong employee sprit and cooperation											^*
	Macro social performance	Macroeconomic welfare									^*
		Monitoring									^*
		Legislation and enforcement									^*
	Conducive work environment	Repetitiveness of the job											^*
		Ability of managing diversification	^*
		Level of automation of the job		^*
	Excitement or boredom felt whilst doing the job	Effective use of job rotation policy											^*
		Assignment of diversified work											^*
		automation of repetitive job											^*

Notes: 1. Aydın Keskin, Ilhan, and Ozkan (2010); 2. Beskese, Kahraman, and Irani (2004); 3. CEC (2002); 4. Dubey and Veeramani (2011); 5. Guneri, Ertay, and Yucel (2011); 6. Kuo, Wang, and Tien (2010); 7. Mamic (2005); 8. McGuire (2000); 9. Vinodh (2010); 10. Spence (2006); 11. Vinodh and Vimal (2012); 12. Vinodh, Jayakrishna, and Joy (2012); 13. Vinodh and Chintha (2011).

The developed model is comprehensive and novel to measure PS. The model is developed by following the three-level model developed by Lin, Chiu, and Chu (2006); Lin, Chiu, and Tseng (2006); Vinodh and Devadasan (2011) for assessing the performance of advanced manufacturing systems. The model has been developed under the pillars of TBL namely environment, economy and society. Enabler encompasses criteria or indicators. Each criterion in turn contains attributes. The criteria and attributes were identified through literature review.

The model consists of three levels. The first level consists of three enablers namely: environmental sustainability, social sustainability and economic sustainability. The second level consists of 30 criteria divided among three enablers. The third level consists of 90 attributes. The meaning of criteria is shown in Table 4. Environmental sustainability mainly deals with energy consumed by the process and negative environmental impact created by the process. The environmental sustainability level was determined by the ability of the organization to prevent, manage and eliminate waste and hazardous substances produced during the process. Social sustainability deals with employee health, employee development and interactions between employee and process. Social sustainability level was determined by the ability to involve and develop employee's interest, measures taken for the precaution of employee health, ability to provide pleasant working environment and finally steps taken in assuring career for employees.

Table 4 Meaning of the criteria.

S. no.	Criteria	Meaning
1.	Flexibility and response to changes	The ability of the organization on how far it is able to adapt to changes and flexible resources availability
2.	Operating controls	Availability of SOPs for various operations and installation of inline process controls
3.	Reciprocal arrangements	The agreement between organizations to share resources and expertise for their mutual benefit
4.	Conflict resolution	Ability to solve conflicts and arriving at some negotiating decision
5.	JIT capability	Ability to implement full-fledged pull system and steps to attain core competency
6.	Maintainability	The ability to maintain processes and resources to enhance productivity
7.	Defect ratio	The total number of defective products produced to the number of products produced
8.	Testing methods	Availability of various inspection and testing methods
9.	Reverse logistics	Ability to recapture materials after their effective life time for proper disposal
10.	Value stream management	Ensure the usage of VSM tools to eliminate various deadly wastes
11.	Management for hazardous substances	Ability of Safe handling, use and transportation of materials and facilities for disposing hazardous wastes
12.	Recyclability	The ability to recycle products, wastes and materials in order to reduce resource consumption
13.	Re-manufacturing, re-usability, re-design	Ability to disassemble, recondition and re-assemble used products
14.	Environmental management	Awareness of scientific tools/techniques and availability of in-house technologies and principles to optimize resource consumption
15.	Pollution prevention and control aspects	Steps to reduce water usage, control and treatment of water effluents released
16.	Carbon footprint	Quantification of CO2 and other gases released by the organization to the atmosphere
17.	Waste management	Measure the appropriate usage of waste collection mechanism to segregate and dispose wastes
18.	Energy conservation	Awareness towards energy consumption, conduct of energy audit and ability to generate and use renewable energy
19.	Environmental friendliness	Ability to develop cleaner technologies, effective training sessions for energy conservation and usage of eco-friendly materials
20.	EoL disposal	Measures taken to reduce land fill and ability to use cleaner mechanism for disposal of wastes
21.	Resource usage	Effective utilization of minerals and other natural resources consumption
22.	Green image	Development of eco-friendly products to maintain green image to attract wider customers
23.	Employee compensation practices	Methods and practices involved in the compensation (salary, perks, increments) provided to the employees
24.	Enforcement for socio-environmental performance	Conduct of awareness programme about government regulations and environmental policies
25.	Implication of health hazards and its practices	Practices employed to enhance health and safety of the employees for the well-being of their career
26.	Employee career development programme	Practices deployed to maintain discipline within the organization and conduct of career development programme for the benefit of employee
27.	Employee involvement	Ability to involve employee in various decision-making activities by encouraging through appraisal schemes
28.	Macro social performance	Monitoring of social performance and contribution by the organization to the local economy
29.	Conducive work environment	Ability to engage operators in interesting jobs and automation of repetitive mechanized work
30.	Excitement or boredom felt whilst doing the job	Conduct of games and cultural sessions to eliminate monotonous working culture

Note: VSM, value stream mapping.

3.1 MGF approach

PS assessment using the MGF approach consists of three levels. The expert team used the scale given below for assessing attributes with single factor vector. The scale used was divided into five grades since the PS factor involves fuzzy determination.

where MGF represents multi-grade fuzzy approach; R, performance rating obtained from expert team, 8–10 represents ‘extremely sustainable’, 6–8 represents ‘sustainable’, 4–6 represents ‘generally sustainable’, 2–4 represents ‘not sustainable’ and less than 2 represents ‘extremely sustainable’ (Vinodh 2010; Yang and Li 2002).

At primary level, single factor vector and weights obtained from expert team were used. The weights obtained from the expert team should follow the condition given in Equation (1). Using Equation (2), single factor vector for the criterion level will be obtained.

(1)

(2)

where represents weights obtained from expert team; , performance rating for kth attribute obtained from nth expert; , single factor vector obtained from expert team.

At the secondary level, weights obtained for each criterion from the expert team and single factor vector obtained from primary level calculation were used. Using Equation (2), single factor vector for tertiary level was obtained. During tertiary level assessment, PS level of the organization was obtained. It is the product of overall single factor assessment vector (R) obtained during secondary level assessment and overall weight (W) obtained from the expert team. The PS level single factor vector was calculated using Equation (3).

(3)

where is PS single factor vector, is process sustainability; assessment vector – value obtained from experts in the form of multi-dimensional array.

The single factor vector was converted into crisp values using Equation (4)

(4)

where is process sustainability index; n, the number of experts.

3.2 Computation of performance importance index (PII)

Lin, Chiu, and Chu (2006) proposed a method for identification of drag factors using the fuzzy logic approach. We adopted the method with a minor modification to suit the MGF approach, and using this method, the drag factors were identified. Performance importance index (PII) is the product of single vector factor and weight for each PS criterion which represents an effect which contributes to the PSI level of the organization. The higher the PII of a factor is, the lower the degree of contribution for this factor is.

If is high, then the transformation [(10, 10, 10, 10, 10) − R_ij] is low. Consequently, for each PS criterion capability ij, PII_ij, is defined as

(5)

where is the performance importance index for jth criterion in ith enabler, is complement of performance index of kth attribute given by nth expert.

4. Case study

This section describes the details about the case organization and PSI assessment.

4.1 Organizational profile

The case study was conducted in a rotary switch manufacturing organization situated in Coimbatore, Tamil Nadu, India. The products manufactured by the organization include rotary switches, modular switches and relays. The organization has implemented world class manufacturing strategies such as ISO 9001:2000 quality management system and ISO 14001 environmental management systems. A total of 350 employees are working in the organization and the current turnover is 250 million Indian rupees ( ≈ 4.6 million USD). The organization is following supply chain management practices by means of outsourcing certain components of product assembly. Also, the concept of reverse logistics is being followed. The standards for quality testing are being followed effectively with appropriate operating controls. Also, the organization has flexible characteristics to respond to changing market conditions. Mutual sharing and exchange of resources are in practice in the case organization. The eco-friendliness of the product is being improved by conducting environmental impact analysis on each and every product of the case organization during the early design stages of new product development. Incentives and rewarding schemes are being followed to encourage employee involvement in problem solving. IT-based utilities are being used for effective communication and data storage with the organization. Training sessions on safety operations are being conducted for employees to understand the importance and need for following safety practices. These are some of the sustainability characteristics prevailing in the case organization.

4.2 Need for the study

The organization plans for environmentally benign manufacturing process with specific focus on PS improvements which motivates the conduct of the study. The expert team decided to use a scientific approach to compute the PSI level and to systematically find the drag factors which form the obstacles to sustainability. So there exists a need for the development of conceptual models in focus with process orientation.

4.3 Expert team

The experts are the heads of various departments namely Design, Production, Quality Control, Research & Development and Customer Service in the organization. The decision-makers possess excellent and rich experience on the manufacturing processes being carried out in the organization. An interaction session was held for experts along with the research team to enhance knowledge about assessment and conceptual model. Experts were asked to assess the performance rating and weights of PS capabilities using linguistic variables.

4.4 PS assessment using MGF approach

This section describes the various steps involved in the assessment of PS.

4.4.1 Inputs for PS assessment

The expert team participated in the sessions for the assessment of sustainability of process orientation. The expert team used the scale {10, 8, 6, 4, 2} to measure single vector factor for attributes and used a scale between 0 to 1 to measure the weights of attributes, criteria and enabler. The input measures given by the expert team for economy enabler are given in Table 5.

Table 5 Excerpt of weights and performance rating.

				Performance ratings
Enabler	Criteria	Attribute	Weights	E1	E2	E3	E4	E5
Economic sustainability	Flexibility and response to changes	Production flexibility	0.5	8	7	8	7	8
		Market flexibility	0.3	9	8	8	9	8
		Retrofitting of machine tools	0.2	8	7	8	7	8
	Operating controls	Development of SOP	0.5	9	9	8	9	9
		Monitoring and observation of equipment performance	0.3	8	9	8	7	8
		Operation controls activated through in-line monitoring	0.2	8	7	8	7	8
	Reciprocal arrangements	Two organizations to back each other up	0.3	8	7	9	8	7
		Two organizations to use each other's resources	0.3	8	7	7	6	7
		Rendering assistance to each other	0.4	7	8	8	6	5
	Conflict resolution	With suppliers	0.3	5	6	6	6	5
		In workplace	0.4	7	6	5	7	6
		With customers	0.3	8	7	8	9	8
	JIT capability	Pull system	0.4	9	8	7	8	6
		Lead time	0.3	9	8	7	8	6
		Building core competence	0.3	6	5	5	6	5
	Maintainability	Analysis of repetitive equipment failure	0.4	6	7	7	6	6
		Evaluation of maintenance cost and alternatives	0.3	8	7	6	7	6
		Formation of new strategies to prevent failure	0.3	9	8	7	6	7
	Defect ratio	Proper inspection plan	0.3	7	8	9	8	7
		Quality improvement programme	0.4	8	9	7	6	7
		Professional techniques	0.4	8	6	7	6	7
	Testing methods	Availability of testing equipment	0.3	8	9	7	6	8
		SOP for testing	0.4	8	9	9	8	7
		Efforts to improve testing efficiency	0.4	8	6	6	8	7
	Reverse logistics	Uncertainty in material recovering	0.4	7	8	9	8	7
		Reverse logistics network	0.3	7	6	8	7	6
		Stochastic routing problem	0.3	8	9	8	7	6
	Value stream management	Adaptation of value stream mapping	0.5	6	5	5	7	6
		Elimination of deadly wastes	0.3	5	6	6	5	6
		Adaptation of processes for better vendor–supplier relationship	0.2	7	6	8	7	6

The summation of the weights of attributes within the criteria should be 1. The experts were asked to satisfy Equation (1) while providing the weights. Further using Figure 2, fulfilment of this condition was ensured for all attributes. The weights given by the expert team should satisfy Equation (1) and its satisfactory level is shown in Figure 2 for attributes of economic enabler. Similarly weights were obtained for other enablers and were checked for satisfaction of Equation (1).

Figure 2 Chart represents satisfaction of input weights.

4.4.2 Assessment of PSI

This section explains the primary, secondary and tertiary assessments using the MGF approach.

Primary assessment calculation

The sample calculation pertaining to attribute ‘Flexibility and response to changes’ criterion is shown below. The attributes of ‘Flexibility and response to changes’ criterion include production flexibility, market flexibility and retrofitting of machine tools.

Weights pertaining to attributes of ‘Flexibility and response to changes’ criterion are given as

Assessment vector pertaining to attributes of ‘Flexibility and response to changes’ criterion is given by

Using Equation (2), single factor vector for ‘Flexibility and response to changes’ is calculated as:

Using the same principle, the indices pertaining to other criteria have been calculated.

Secondary assessment calculation

The sample calculation pertaining to criteria of ‘Economic sustainability’ enabler is shown as follows:

Weights pertaining to criteria of ‘Economic sustainability’ enabler are given as

Assessment vector pertaining to ‘Economic sustainability’ enabler is given by

Index pertaining to ‘Economic sustainability’ enabler is calculated using Equation (2).

Using the same principle, the results have been obtained for environmental sustainability and social sustainability enablers.

Tertiary assessment calculation

The composite value of PSI is computed as follows:

Overall assessment factor

PS single factor vector is calculated using Equation (3).

The PSI is calculated using Equation (4).

5. Results and discussions

The sustainability index computed using the MGF approach is found to be 6.94. This belongs to the range (6–8), PSI is found to be Sustainable'. Gap analysis was done to identify the drag factors. In order to identify the principal obstacles for improving PS level, gap analysis was done. Using Equation (5), value for criterion was computed. A PII, which combines the performance rating and weight of each criterion, was used to identify the associated drag factors. Then using Equation (4), the calculated is converted into crisp number. The lower the PII of a criterion is, the lower the degree of contribution for this factor is. To identify critical obstacles, value 3.5 was set as the management threshold in consultation with the expert team. Based on Figure 3, critical criteria were identified. In total, eight criteria were identified to possess lower score than the threshold value.

Figure 3 Performance importance index.

5.1 Practical implications

From Figure 3, it is found that criteria just-in-time (JIT) capability, pollution prevention and control aspects, value stream management, green image, resource usage, energy conservation, implication of health hazards and its practices, and conducive work environment have lower performance than the management threshold limit. The improvement proposals for further improving PS level fulfilled the claim that the developed model has practical relevance.

For this, a dedicated sustainability team with the focus of initiating sustainability improvement was formed. The team includes members from various levels of the organization. The team was trained by experts by conducting an interaction programme on fundamentals of sustainable manufacturing. The improvement proposals for drag factors are presented in Table 6. The improvement proposals were identified in consultation with the expert team. The expert team participated in the sessions for identification of improvement proposals. Then the project charter was created for each of the improvement activity. The charter includes team leader, team members, objective of the activity and project duration.

Table 6 Improvement proposals.

S. no.	Weaker area	Improvement proposal
1.	JIT capability	Kanban system can be implemented to prevent the idle time in the process flow
2.	Pollution prevention and control aspects	Steps have been taken to implement pollution control norms across all manufacturing process
3.	Value stream management	Environmental conscious VSM which includes materials usage by process, materials needed for product; pollution and other environmental wastes generated are being mappedInformation flows could also be used to stream line flow
4.	Green image	The organization plans to release annual sustainability reportTools and techniques followed to improve sustainability were made available for customer and supplier referenceCross functional team has been formed to implement sustainable manufacturing among all suppliers
5.	Resource usage	Teams were formed to measure the recourses usage along the supply chain. Tools like environmental conscious VSM can be used to ensure optimal usage of resource
6.	Energy conservation	Steps will be taken to conduct energy audit. Policies followed by competitor will be adopted in near future to reduce energy consumption. Scope for renewable energy generation will be explored
7.	Implication of health hazards and its practices	Awareness programme were conducted among employee, for them to use safety and health hazard prevention devices. Supervisors were requested to insist the benefits of using safety practices
8.	Conducive work environment	Games and cultural session will be conducted in future to eliminate the monotonous work culture. Employee will be trained in diversified work in near future

5.2 Managerial implications

The approach for PS assessment proposed in this study enables the practicing engineers and managers to comprehensively assess the PS level of their organizations. Besides the computation of PSI, the approach enables the managers to systematically identify the drag factors, which are the obstacles to sustainability improvement. In this context, modern managers can help the organizations to be competitive in ensuring environmentally conscious practices by adopting this methodology.

6. Conclusions

Sustainable development in a manufacturing firm can be achieved by three orientations such as material, product design and manufacturing process. Among these, process dimension gains more importance as it directly contributes to the energy conception, emission, etc. So PS level needs to be evaluated in order to stay competitive and to cope with the new government regulations. Sustainability refers to the capability of an organization to maintain environmental safety and minimize negative environmental impact. This article reports a case study in which PSI has been assessed using a comprehensive 30 criteria model. By using the MGF approach, the current PSI level has been assessed as Sustainable. Then PII has been computed to identify the drag factors and to identify improvement measures. After the implementation of the improvement proposals, PSI level will be expected to be improved significantly.

6.1 Limitation and future research directions

The model was developed for assessing the PS of the case organization. The 30 criteria model could be further expanded similarly by including process parameters and other variables similar to GREENSCOPE model proposed by Ruiz-Mercado et al. (2012). This conceptual model can be made generic by conducting studies in different organizations. Due to impreciseness and vagueness on sustainability assessment, the MGF approach can be replaced with advanced fuzzy logic approaches such as Fuzzy logic, Fuzzy Kano model and human inference-based approach. Artificial intelligence approaches can also be incorporated to eliminate repetitive work.