Modelling, assessment and deployment of strategies for ensuring sustainable shielded metal arc welding process – a case study

Journal of Cleaner Production xxx (2015) 1e14

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Modelling, assessment and deployment of strategies for ensuring sustainable shielded metal arc welding process e a case study K.E.K. Vimal a, *, S. Vinodh a, A. Raja b a b

Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India Welding Research Institute, Bharat Heavy Electricals Limited, Tiruchirappalli, Tamil Nadu, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 19 June 2014 Received in revised form 15 January 2015 Accepted 15 January 2015 Available online xxx

The welding process is viewed as an environmentally vulnerable due to its energy intensive nature, human hazards and environmental burden. But, the deployment of sustainable manufacturing strategies (SMSs) can improve the sustainability of the welding processes. In this study, shielded metal arc welding (SMAW) process is considered as a candidate process for which the influence of implementing SMSs on sustainable performance was studied. Using the graph theory approach, interdependence among the Sustainable Manufacturing Measures (SMMs) was modelled to assess the SMSs. Based on the study, two SMSs, namely, employee skill training and involvement program, and waste minimization and disposal strategies were resorted to. The waste minimization and disposal strategy resulted in improved environmental performance and conservation of materials. Based on the findings, manufacturing organizations will be motivated to initiate sustainable manufacturing practices in their processes. This study also appreciates the application of modelling approach in sustainability studies from an economic point of view. Further, the study extends the scope of welding research to sustainable process optimization and redesigning. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Sustainable manufacturing Sustainable manufacturing strategies Sustainable manufacturing measures Welding process Graph theory

1. Introduction Government legislation is the main reason for organizations implementing sustainable manufacturing practices. Kaebernick and Kara (2006) believed that apart from government legislation, factors like economic benefits, long term survival in the market, environmental responsibility, green competitive advantage and green image are other reasons to implement sustainable manufacturing practices. These benefits are the major reasons restructuring organizations stake on sustainable development. Modern economic revolution largely focused on process improvement which is different from old economic policies that largely rely on product development strategies. Like other advanced manufacturing strategies, sustainable development concepts also coped with the above shift. Unlike product development, a dedicated methodology (Kaebernick et al., 2003; Ljungberg, 2007) to improve process sustainability characteristics is missing. Vimal and Vinodh (2013), Rubin et al. (2014) and Culaba

* Corresponding author. E-mail address: [email protected] (K.E.K. Vimal).

and Purvis (1999) contributed the assessment and alternate process selection methodology to ensure better process sustainable characteristics. But, pollution prevention in the manufacturing processes through appropriate studies, does not exist. Shielded Metal Arc Welding (SMAW) is a popular metal fabrication process in construction, shipbuilding operations and metal structure industries. SMAW was used for welding stainless steel, high-carbon steel, copper, brass, and even aluminium (Goel et al., 1993). The arc developed in the air gap between electrode and the base metal melts the electrode which is deposited over the base metal. In SMAW process, the electrode wire is surrounded by a coating of mineral and organic components (Goel et al., 1993). Burning flux creates a cloud which surrounds the arc and protects the welding area from oxidization. Flux is the main reason for the formation of dust and other process wastes. In the past, researchers contributed sustainability assessment (Yeo and Neo, 1998), environmental assessment (Amza et al., 2010) and other characterization studies for welding processes (Zimmer and Biswas, 2001). These studies may help to understand the prevailing nature; but to improve the environmental performance of welding process, sustainable strategies need to be resorted to. In literature, steps to

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Please cite this article in press as: Vimal, K.E.K., et al., Modelling, assessment and deployment of strategies for ensuring sustainable shielded metal arc welding process e a case study, Journal of Cleaner Production (2015), http://dx.doi.org/10.1016/j.jclepro.2015.01.049

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develop and deploy strategies specific to particular manufacturing process are missing. Thus, the major challenge addressed in this study is to understand the welding process from a sustainability point of view, and to develop the Sustainable Manufacturing Strategies (SMSs). Thus, the deployment of SMSs is expected to achieve the objective of reducing the environmental burden of a SMAW process. But, it is practically infeasible to deploy all the identified SMSs as the deployment of SMSs involves significant human effort and time and economic investment. Devoting more human hours toward the deployment of environmental strategies are not usually appreciated by top level managements. So, a suitable SMS is identified after assessment using Sustainable Manufacturing Measures (SMMs). SMMs are the indicators to quantify the importance or contribution of SMSs toward improvement of process sustainability characteristics (triple bottom line perspective). Hence, the objectives formulated in this study include:
To identify SMMs which include environment, economic and social dimensions of sustainability
To develop SMSs based on a literature review and experts' understanding of the SMAW process
To develop a methodology to model, assess and deploy SMSs for the manufacturing process
To examine the practical feasibility of the proposed method Thus, attempting the above objectives results in:
Proper understanding of the SMAW process from a sustainability point of view
Identification and selection of most important SMSs considering SMMs
Deployment of SMSs in the SMAW process which was not attempted in the past
To ensure a path to development and designing of manufacturing processes considering sustainability characteristics The paper is organized in seven sections. In Section 1, background and the formulated objectives are summarized. Section 2, reviews literature from the perspectives of SMMs, sustainable manufacturing practices in the welding process and SMSs are detailed. Section 3, deals with problem details and descriptions about the graph theory approach, SMMs, SMSs and a plan of deployment of SMSs. The proposed methodology is detailed in Section 4. The case study and results are presented in Section 5. Conclusions, limitations of the study and future prospects are presented in Section 6. 2. Literature review Welding processes form the backbone of metal fabrication industries (Goel et al., 1993). On the other hand, welding processes are prone to have adverse effects on human health (Antonini, 2003; Zukauskaite et al., 2013) and environment due to of aerosol and Greenhouse Gasses (GhGs) emitted (Yeo and Neo, 1998). Few initiatives were attempted to analyse welding processes from a sustainability viewpoint (Zukauskaite et al., 2013; Drakopoulos et al., 2009). Thus, the first two modules of literature are reviewed from the perspectives of sustainability studies in the welding process and SMSs. The implementation of effective practice may ensure better sustainability characteristics compared to other practices. The effect of particular SMS can be measured using SMMs (Veleva and Ellenbecker, 2001). Hence, the third module of literature review is on SMMs.

2.1. Sustainable manufacturing practices in welding process Welding process does not possess a great environmental image largely due to dust, gases and process wastes i.e. slag in Submerged Arc Welding (SAW), stub in SMAW and spatter in almost all welding processes. Yeo and Neo (1998) state that, around 1% of consumables are converted into emissions. Four chemical components present in electrode coating are: gas generators, slag producers, alloying substance and binders (Steel and Sanderson, 1966). But, welding is an important process in metal fabrication which cannot be replaced. Thus, a step toward improving the environmental performance of the process needs to be studied. The review of past literature towards enhancing environmental performance of the welding process is presented as follows: As a consequence of the growing importance of environmental consciousness, Yeo and Neo (1998) addressed the importance of environmental performance in welding process selection. Using Analytic Hierarchy Process (AHP), a health hazard score was computed based on process emission data. With the developed methodology, SMAW and Metal Inert Gas welding (MIGW) processes were assessed. Zimmer and Biswas (2001) developed a characterization model for aerosol related to SMAW and Flux Cored Arc Welding (FCAW) processes. With the developed apparatus, steady state arc was attained by varying the process parameters. The investigation suggested that welding alloy has a greater influence on particle size, morphology and the chemical distribution of the resultant fume. Amza et al. (2010) conducted environmental assessment of the gas welding process. The pollution coefficient was defined based on a work environment of the welding process. With rigorous experiments, fumes of various oxy acetylene welding processes were characterized. Drakopoulos et al. (2009) conducted an environmental analysis on welding processes, namely SAW, Plasma Arc Welding (PAW), SMAW, Oxyacetylene Cutting (OAC) and FCAW. By applying Life Cycle Assessment (LCA) methodology, various environmental impacts were assessed using the Eco-indicator'99 characterization model. The assessment suggested that, automatic welding processes namely, SAW and PAW are more environmentally-friendly than manual processes. Among manual welding processes, SMAW is 70% more environmentally-friendly than the other two processes. Zukauskaite et al. (2013) validated the same with respect to a human health hazardous criterion. Using GaBi 5 LCA package, four processes, namely SAW, SMAW, FCAW and MIGW were compared, and the result favoured SAW. As far as the SAW process is concerned (Mahto and Kumar, 2010), the problem is storage and disposal of wastes, and environmental pollution apart from the exhaust of non-renewable resources. The flux used in SAW after use generates wastage known as slag. Regarding economic terms, the possibility of recycling the slag was explored with its associated environmental benefits. This was also addressed by Singh and Pandey (2009). The above review uncovers various environmental conscious studies on welding processes. But, from the above review it can be concluded that, pollution prevention or improvement studies have not been largely attempted. 2.2. Sustainable manufacturing strategies Rusinko (2007) said pollution prevention was an important strategy, which implies a method to trap, store, treat and dispose pollutants. Seidel et al. (2007) identified sustainable manufacturing strategies which can be viewed in two loops, namely material cost and process investment loop. The process investment loop minimizes waste and improves energy efficiency. Apart from environmental benefits, waste minimization and improved energy efficiency have a positive influence on an organizations' bottom line.

Please cite this article in press as: Vimal, K.E.K., et al., Modelling, assessment and deployment of strategies for ensuring sustainable shielded metal arc welding process e a case study, Journal of Cleaner Production (2015), http://dx.doi.org/10.1016/j.jclepro.2015.01.049

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Kaebernick and Kara (2006) conducted a survey of environmental practices followed by manufacturing organizations and concluded that old economies were more focused on product development, whereas a shift was experienced in modern economies that focus on the manufacturing process. In product perspective, End-of-Life (EoL) strategies gain more importance in recent times because of the scarcity of material. In early days, there were abundant resources and organizations found difficulties in allocating the required manpower. Now, globalization and other economic revolutions focus on resources like material and energy. Rashid et al. (2008) compared four SMSs which improved material performance. Those four strategies include: waste minimization, material efficiency, resource efficiency and eco-efficiency. These strategies were compared in terms of definition, scope, practicality and compatibility. Also, Garetti and Taisch (2012) emphasized the importance of resource and energy management, and facilitating newer technology for successful implementation of sustainable strategies in the manufacturing scenario. The above review suggested the importance of material and resource efficiencies, and pollution control for effective implementation of sustainable practices in manufacturing organizations. A few strategies are focused on pollution prevention and the others on pollution control. 2.3. Background of sustainable manufacturing measures The Lowell Center for Sustainable Production (1998) (LCSP) defined sustainable production as the (1) creation of goods and services using processes and systems that are non-polluting; (2) conservation of energy and natural resources; (3) economically viability; (4) safe and healthy for employees, communities and consumers; and (5) socially and creatively rewarding for working people. The above definition is claimed to be consistent with triple bottom line by Veleva et al. (2001) and Tseng et al. (2009). However, the performance of a manufacturing unit as defined by LCSP needs to be assessed using sustainable manufacturing measures (Veleva and Ellenbecker, 2001; Lin et al., 2010). Hence, the identification of measures is important to enable sustainable manufacturing (Tseng et al., 2009). In the past, literature evidenced the interchangeable use of term indicators with measures (Sikdar, 2003). Veleva et al. (2001) stated that ‘measures’ provides trends of factors assessed, and its relationship with organizational performance. In general, performance assessment helps to raise awareness, decision making and progress toward a defined goal. The number of sustainable manufacturing measures increases, as scope for sustainable manufacturing grows due to green competitive pressure due to globalization (Tseng, 2013). Veleva et al. (2001) proposed an evaluation method using a set of indicators focussing on environmental, health and the safety aspects of production. Also, goal, calculation method and derivation of inferences were explained for identified 22 indicators to support decision makers. Veleva and Ellenbecker (2001) outlined a method to use the developed set of indicators. Schwarz et al. (2002) used five metrics of sustainability to assess and compare the performance of alternative processes. The five metrics include: material intensity, energy intensity, water consumption, toxic emissions and pollutant emissions. Tseng et al. (2009) used Sustainable Production Indicators (SPIs) to measure the environmental performance of a multinational original equipment manufacturer. A quantitative evaluation model which considers interdependency and feedback was developed using Analytic Network Process (ANP) methodology. This model was adopted by Lin et al. (2010) for strategic operating decisions in the area of production process improvement toward sustainability. Tseng (2013) used a novel fuzzy based interpretative structural

3

modelling approach to model interaction of SPIs. Based on the derived hierarchy, indicators were arranged in visual quadrants and classified into driving and dependent indicators. The proposed visual quadrants help managers derive strategic planning for a firm's environmental activities. However, Veleva and Ellenbecker (2001) disagreed over the possibility of a consensus set of SPIs being applicable to all kinds of manufacturing processes. Also, Tseng (2013) stated, that even though indicators in literature were growing, economic aspects are not addressed. The above-mentioned literature suggested the evidence of sustainability in a welding process. Most studies focus on measurement and characterization of environmental pollution due to welding processes. However, evidences on deployment of sustainable practices dealing with important environmental issues are missing. The studies on most important issues like disposal of active components, and optimization of resources to enable pollution prevention are missing. It is clear that no study was conducted to improve the overall sustainability of welding processes. Thus, the outcome of this study is expected to fill this gap. 3. Problem statement This article describes a case study conducted in Welding Research Institute (WRI) e Bharat Heavy Electricals Limited e Tiruchirappalli (BHEL-T), India. WRI as a national institute supports BHEL-T and other manufacturing concerns across India in fabricating new materials, metallurgical analysis and other advanced services through dedicated research laboratories. WRI is currently working with the aim of becoming a world class research institute. In line with the above objective, WRI has initiated environmental studies. The studies aim to improve the environmental performance of a welding process and working atmosphere in Indian industries. Widely used semi-automatic welding processes in India include: FCAW, Tungsten Inert Gas Welding (TIGW), SMAW and MIGW. All the four processes are vulnerable to environment because of gaseous emissions and other process wastes. The gasses generated during SMAW process include: CO, NO2, H2, SO2 and H2S (Amza et al., 2010). Another important waste in SMAW process is ‘The short length of filler metal electrode that remains in electrode holder after its use for welding’ (AWS A3.0:2001). This is defined as ‘stub’ by the American Welding Society (AWS). Stub is a portion of the electrode which contains uncoated portion (core wire) and a coated portion. Other three semi-automatic processes (FCAW, TIGW and MIGW) are free from stub as they use continuously fed feed wire. The average length of the stub in SMAW process is 50 mm in which 25e30 mm is coated with flux. The coated flux contains active components like slag formers which to provide improved resistance to crack and porosity. Stub cannot be reused, and so needs to be disposed. At present in WRI, stubs are disposed through landfills. Among semiautomatic welding processes, the SMAW process Shares up to 65e70% in Indian metal fabrication organization (Raja et al., 2012). Thus, improvement studies in widely applied welding process may better contribute to the environment. In this view, SMAW was selected as the candidate process for an environmental performance improvement investigation. In SMAW process, an electrode has a metal core, surrounded by a coating containing mineral and organic components. The coatings are complex and various components which are used are moulding agents, extruding agents, binders, fibrous materials, slag formers and metal powders (Steel and Sanderson, 1966; Yeo and Neo, 1998). The strategies involve process emission reduction, parametric optimization, energy modelling, training program and waste minimization. Considering the practice of SMAW process in WRI, a suitable SMS was identified in consultation with an expert team and literature support.

Please cite this article in press as: Vimal, K.E.K., et al., Modelling, assessment and deployment of strategies for ensuring sustainable shielded metal arc welding process e a case study, Journal of Cleaner Production (2015), http://dx.doi.org/10.1016/j.jclepro.2015.01.049

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The expert team had a blend of ‘industrial experts’ who possess knowledge of industrial welding processes and their applications; and ‘sustainable manufacturing experts’ who are knowledgeable in sustainable manufacturing implementation in various manufacturing companies. Sessions were conducted among the experts to evolve group synergy. In the interaction, the concept of welding processes and sustainable manufacturing practices were discussed. The motivation was to evolve better understanding among industrial and sustainable manufacturing experts. Once the expert team members gained confidence on the concept and goal of the study, group knowledge was used to evaluate the sustainability of the SMAW process. The details of expert members and their qualification are shown in Table 1. With SMMs, the identified SMSs are assessed. Multi Criteria Decision Making (MCDM) techniques widely used for the selection of alternatives considering the measures include: Technique Ordered Preference by Similarity to the Ideal Solution (TOPSIS), Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), graph theory, AHP and ANP. But, AHP and MCDM techniques lack the ability to compare the interdependency of criteria and their influence on alternative selection, which ANP does. The major shortcoming with ANP methodology is that it considers the problem as a unidirectional, where the real time scenario is different. The consideration of hierarchy relationship in a linear form, strictly from top to bottom is called a unidirectional problem (Shyur, 2006). On the other hand, structural equation modelling can be used but, it requires a large sample size as the exactness of estimates is affected by the sample size (Anbanandam et al., 2011; Muduli et al., 2013). Among the set of decision making techniques, graph theory considers both interdependency and inheritance by overcoming the above mentioned shortcomings (Anand and Kodali, 2010). Thus, graph theory approach was used to model and assess the strategies by using expert knowledge. The basics of graph theory approach and solution method adopted for the assessment are discussed in the following subsections: 3.1. Graph theory approach Graph theory approach is a combinatorial operations research technique, useful for modelling and analysing a system. Graph theory approach comprises the following steps: digraph representation in matrix form and computing permanent value of matrix (Jurkat and Ryser, 1966). The development of digraph is shown in Equation (1).

2

V1 L21 «

6 6 S¼ 6 6 4 Lði1Þ1 Li1

L12 V2 « Lði1Þ2 Li2

… … 1 … …

L1ði1Þ L2ði1Þ « Vi1 Liði1Þ

L1i L2i «

3

7 7 7 7 Lði1Þi 5 Vi

(1)

Table 1 Expert team. S. No

Expert member

Qualification and designation

Expertise

1

Welding Expert (2)

AGM, WRI Tiruchirappalli

2

Sustainable manufacturing expert (2) Engineer (1)

Professor

Various welding process, advanced manufacturing systems and implementation of ISO 14000 systems Sustainable manufacturing systems assessment and implementation Various welding process, Input e Output analysis of welding process

3

Assistant manager

where V e Vertex which represents value of a pair of similar elements (Lij), i ¼ j L e Links which represent value of a pair of distinct elements (Lij), i s j The ‘inheritance’ and ‘interdependency’ are represented in diagonal and edge of matrix respectively. The inheritance is represented by vertex and interdependency by using links in digraph. With matrices, the permanent value of matrix for each alternative is computed similar to determinant computation (with all positive signs). Application of permanent concept leads to better appreciation as no information is lost. Jurkat and Ryser (1966) proposed an approach for computing permanent of matrix S ¼ (sij) with order n > 1. Equation (2) is the general form used to compute permanent function of matrix S (Jerrum et al., 2004). The permanent value is computed using ‘permanentryser ()’ function available in MATLAB package. The index value obtained by calculating the permanent value of multinomial can be used for ranking the alternatives. The graph theory has found varied application as shown in Table 2.

0 perðSÞ ¼ @

XY j

1 SMSi Lij A

(2)

i

SMSie inheritance score of SMSsLij e interdependency scores of SMMs

3.2. Inventory analysis of SMAW process The flow diagram of SMAW process was developed for better understanding of the process and is shown in Fig. 1. Based on the analysis of Fig. 1, the interaction of SMAW process with techno sphere (stub) and eco sphere (fumes, waste heat and slag) are identified. The fumes, solid wastes and stub are the major reasons for environmental vulnerability. To improve sustainability characteristics of the SMAW process, pollution prevention strategies, waste minimization and energy efficiency strategies need to be identified and implemented.

Table 2 Background of application of graph theory. S. No

Authors

Application domain

1

Muduli et al. (2013)

2

Anand et al. (2013)

3

Aravind Raj et al. (2013)

4

Anand and Kodali (2010)

5

Grover et al. (2006)

6 7 8

Singh and Agarwal (2008) Rao and Padmanabhan (2007) Rao and Gandhi (2002)

Assessment of green supply chain management in Indian mining industries Assessed readiness of organization to adopt lean practices Assessed the agility performance of organization Analysed the effect of human factor in Lean environment Analysing the effect of human factors in total quality management environment. Analysis of manufacturing system Rapid Prototyping process selection

9

Rao (2007)

10 11

Darvish et al. (2009). Jangra et al. (2011)

Machinability evaluation of work materials Material selection problem for an engineering component Contractor evaluation and ranking Evaluated the machining of tungsten carbide in EDM

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Fig. 1. Process flow of SMAW process.

SMSs should be developed so that it focuses on controlling, eliminating or reducing the vulnerable flows (fumes, solid wastes and stub) in the environment. The details of SMSs are provided in following subsection. 3.3. Sustainable manufacturing strategies for SMAW welding process Based on the analysis of the SMAW process flow (Fig. 1), the identified waste released to the techno sphere is stub, and wastes released to the eco sphere include: fumes, waste heat and slag. The inputs for SMAW process include: consumables, base metal and electricity. Thus, SMSs are selected so that, it improves the SMAW process, considering all flows. Kleindorfer et al. (2005) suggested employee involvement, material conservation, energy conservation, and emission control as important internal strategies to enable sustainability of organizations. For improving the material utilization, waste minimization, material efficiency, resource efficiency and eco-efficiency are critical (Rashid et al., 2008). But, sustainable manufacturing practices have three perspectives, namely material, system and process (Vimal et al., 2014). In the past, SMSs were developed to improve organizational performance and material sustainability, thus process perspective is mostly not attempted. After analysing the process flow of welding processes and analysing the past literature, five sustainable manufacturing strategies are identified: energy modelling and optimization studies (Kleindorfer et al., 2005; Newman et al., 2012), employee skill training (green strategies) and involvement program (Muduli et al., 2013; Carter and Dresner, 2001), process emission studies (control aerosols and fumes) (Gomes, 2014), process parameter optimization considering sustainability aspects (sustainable selection of process parameters for improving environmental performance) (Yan and Li, 2013; Sivapirakasam et al., 2011) and waste minimization and disposal strategies (to avoid and adapt environmentallyfriendly disposal) (Foolmaun and Ramjeawon, 2008). A brief description of the strategies is presented below. 3.3.1. Energy modelling and optimization studies (SMS1) For metal removal process, 90% of environmental impact is due to electrical energy consumed. As far as the welding process is

concerned, electrical energy consumption was not studied much in the past. Still, literature suggests that welding process is a highly energy intensive process. The environmental performance of the welding process depends on the effective energy consumption during the operational phase. Initiation of measures to improve energy consumption of machine tools provide substantial leverage to reduce associated environmental impact in the use phase. Newman et al. (2012) identified possible ways to improve energy efficiency of the manufacturing process through energy consumption mathematical modelling and energy conscious metal cutting. Gutowski et al. (2006) further studied various electrical energy requirements for the manufacturing process through analysing specific energy requirements. The energy studies are viewed in process, machine, line and factory levels. Many researchers adopt different methods to study the energy consumption and the efficiency of manufacturing process as listed in Table 3. In general, the energy consumption of welding process is highly dynamic in nature. Posselt et al. (2013) studied the power demand of welding operations through metering devices for varied operation modes. With energy and time studies, two welding processes were compared. The energy consumption of SMAW process was studied in the case organization. The energy consumption during the operation phase is measured for an electrode (E7018) of diameter 3.2 mm, with 150 ampere while making a butt joint in a mild steel base. Based on the above study, the need for energy optimization is appreciated. Thus, energy optimization of the SMAW process is planned under this strategy.

Table 3 Various energy modelling methods. S. No Method

Author

1 2 3 4 5 6 7

Duflou et al. (2012) Dietmair and Verl (2009) Herrmann, and Thiede, 2009 Gutowski et al. (2006) Kellens et al. (2012) Rajemi et al. (2010) Seow and Rahimifard (2011)

Energy efficiency of discrete manufacturing Energy based modelling Energy profile creation Thermodynamic analysis Power study Energy optimization Modelling embodied product energy

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3.3.2. Waste minimization and disposal studies (SMS2) In lean manufacturing, wastes originally focused on time, quality defects, and excess inventory aspects (Vimal and Vinodh, 2012). In recent times, due to global warming issues and material scarcity, the term ‘waste’ has been redefined to refer to environmental wastes (Rothenberg et al., 2001). Faulkner and Badurdeen (2014) extended the use of value stream mapping methodology to reduce the environmental wastes. An initiative to minimize waste is viewed as conservation of natural resources. Waste minimization aimed to reduce wastes from raw material and ingredient use, product loss, water consumption and effluent generation, packaging, factory and office consumables, energy consumption and other solids. However, reduction of wastes at source point conserves natural resources, so the focus has shifted to waste control rather than minimization. Thus, reuse, recycling and recovery are also included in waste minimization which was not considered in the earlier definition by the Organisation for Economic Co-operation and Development (OECD) (1998). Gupta (1995) stated that the adaptation of environmentallyfriendly waste disposal operations, have positive correlation with the green image of a product. Natural resource scarcity changed the viewpoint. Anastas and Zimmerman (2006) stated that recycling and waste minimization is a means to achieve sustainability. Foolmaun and Ramjeawon (2008) used LCA methodology to determine environmentally-friendly disposal options for used PolyethylenE Terephthalate (PET) bottles. Thus, the focus of waste minimization and disposal strategy is to conserve material through waste minimization and proper adaptation of disposal scenarios through scientific methods such as LCA and material analysis. 3.3.3. Process parametric optimization (SMS3) In general, optimization of process parameters and resources has a trade-off with productivity and quality. Helu et al. (2011) stated that process precision is another factor influencing the use of phase environmental impact of processes. However, the optimization has positive correlation with GhGs emission, energy consumption and waste (Yan and Li, 2013). In the past, most parametric optimization studies were conducted with the objective of improving energy efficiency (Duflou et al., 2012; Rajemi et al., 2010; Jayal et al., 2010). On the other hand, apart from energy consumption, Sivapirakasam et al. (2011) optimized parameters like consumables consumption, aerosol and process time to improve the environmental performance of electric discharge machining process. Guerreiro et al. (2014) characterized the ultrafine particles emitted during metal active gas welding (Ar þ CO2). Through the conduct of this study, the authors highlighted the influence of the current intensity on generated particles. They concluded that, there existed a positive correlation between current intensity and fume formation rate which influenced particle generation. Thus, issues of SMAW process like aerosol, fumes, consumable consumption has to be studied apart from energy optimization. Further, for optimizing parameters, either MCDM (Sivapirakasam et al., 2011) or LCA is to be used (Azapagic and Clift, 1999). 3.3.4. Process emission studies (SMS4) The percentage of GhGs emitted indicates the contribution of an organization to global warming, ozone depletion and eutrophication (Azzone and Noci, 1998). So, steps have to be taken to reduce the generation of GhGs. Rashid et al. (2008) states that the damage to environment can be minimized by reducing emissions. Lee et al. (2014) proposed a methodology to simultaneously consider GhGs emission and ‘use’ phase energy consumption for

the development of eco-friendly products. Azzone and Noci (1998) state that process efficiency indices aimed to assess air emissions. Also, SPI proposed by LCSP (1998), included GhG intensity and air emission as important indicators to assess a manufacturing process. Fumes produced in welding processes are the main cause for the ill image of welding processes. Yeo and Neo (1998) state that, around 1% of consumables are converted to emissions including chemicals, particulates and GhGs. GhGs include: CO2, CO, NO, NO2, and O3. Thus, proper aerosol and fumes studies (Gomes, 2014) are planned to improve human health and the environmental performance of the SMAW process. 3.3.5. Employee skill training (green strategies) and involvement program (SMS5) Employee training and involvement are an important strategy when deploying an advanced manufacturing system. People around the world started recognizing the non-sustainable nature of current economic development trends. Public awareness, education, and training are the key strategies to move society toward sustainability. Earlier few studies pinpointed the importance of employee training and involvement (Vimal and Vinodh, 2012; Muduli et al., 2013). Klassen and Whybark (1999) identified employee training as one of the important tools to incorporate environmental strategies. Shen et al. (2007) used staff factor as an important criterion to deploy sustainability in a manufacturing environment. Training was seen as a solution for environmental problems by many researchers (Walker et al., 2008; Muduli et al.,

Table 4 Sustainable manufacturing measures (SMMs). S. No SMMs

Notations References

1

Health and safety of operators

SMM1

2

Waste intensity of process

SMM2

3

GhG intensity

SMM3

4

Manufacturing SMM4 economy of process

5

Water footprint

SMM5

6

Carbon footprint

SMM6

7

Energy intensity

SMM7

8

Use of hazardous substances

SMM8

9

Recyclability of wastes

SMM9

10

Social Benefits

SMMA

Moneim et al. (2013); Joung et al. (2013); Tseng et al. (2009); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Veleva and Ellenbecker (2001); Tseng et al. (2009); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Veleva and Ellenbecker (2001); Tseng et al. (2009); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Veleva and Ellenbecker (2001); Tseng et al. (2009); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Veleva and Ellenbecker (2001); Tseng et al. (2009); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013) Moneim et al. (2013); Joung et al. (2013); Veleva and Ellenbecker (2001); Tseng et al. (2009); Lin et al. (2010); Veleva et al. (2001); Tseng et al. (2013)

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2013; Carter and Dresner, 2001). Other research studies highlighting the importance of employee involvement and training program include: Tseng et al., 2013; Little and Green, 2009; Rusinko, 2007 and many more. Education, public awareness and training are the core aspects of sustainable development. The training scheme planned for the current study consists of two modules: basic training includes reducing waste, avoiding spills, conserving energy, etc. and advanced training includes awareness of sustainable manufacturing. Education is an essential tool to achieve sustainability. In this study, the education and training strategy helps to develop tools and training for other strategies namely: energy modelling and optimization studies, waste minimization and disposal studies, process optimization and process emission studies. 3.4. Sustainable manufacturing measures (SMMs) Considering the review on SMMs, 10 which were appropriate for assessment and comparison of SMSs for welding processes are identified and presented in Table 4. The identified SMMs cover all three orientations of sustainable development (society, economy and environment).

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4. Proposed solution methods The methodology developed for ranking SMSs considering SMMs is shown in Fig. 2. The steps in graph theory based modelling assessment and deployment of SMSs (Fig. 2) are detailed as follows. Step 1: Identification of SMSs applicable for the SMAW process based on literature review and knowledge of the expert team (Subsection 3.3) Step 2: Identification of SMMs based on literature review (Subsection 3.4) Step 3: Development of universal digraph using graph theory modelling to represent SMMs interactions: Compared to other MCDM techniques, graph theory has the advantages of visualizing the interrelationships and representing a digraph in matrix form which helps mathematical computations. Thus, a universal digraph is prepared with SMMs to assess SMSs. The universal digraph is configured after collecting the knowledge of the expert team. Step 4: Configuration of interaction matrix structure and representation of interdependency: To represent interaction, a square matrix is configured. Then, interaction identified in the universal diagraph is marked in non-diagonal position and ‘0’ is

Fig. 2. Proposed solution methodology.

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Table 5 Scale used for assessing interdependency (Anand and Kodali, 2010). Scores

Linguistic variable and its description

1

Criteria A does not affect criteria B, then it is designated as very weak Criteria A does influence criteria B but does not affect its progress, then it is designated as weak. Criteria A does affect criteria B, then it is designated as medium Criteria A does influence criteria B, then it is designated as strong Criteria A does strongly influence criteria B, then it is designated as very strong

2 3 4 5

Table 6 Scale used for assessing inheritance (Saaty, 1980). Scores

Linguistic variable

1

Extremely low Low

3 5 7 9 2,4,6,8

Description of scores used

Assessed strategy does not help to improve performance of particular criteria. Assessed strategy has least influence towards improving performance of particular criteria Average Assessed strategy influences towards improving performance of particular criteria High Assessed strategy is necessary to improve performance of particular criteria Extremely Assessed strategy has huge impact towards high the performance of particular criteria Represent intermediate values

substituted for position where interdependency does not exist. The matrix helps to compute scores for SMSs. Then, scale shown in Table 5 adopted from Anand and Kodali (2010) is used to represent interdependency relationship. The same was used by researchers elsewhere (Jangra et al., 2011; Grover et al., 2006). It is a five-point scale to analyse the interdependency among SMMs during the assessment of SMSs. The description pertaining to each score is explained in Table 5.

Step 5: Inheritance scores obtained from expert team using scores shown in Table 6: Table 6 was adopted from Saaty (1980) which was predominantly used to measure the performance of alternatives using AHP. This is popularly called Saaty-scale and was successfully used by many researchers during the evaluation of manufacturing processes (Agarwal et al., 2006; Jangra et al., 2011) and other applications (Wu, 2008; Grover et al., 2006). Graph theory approach also extends the application of Saaty scale for the assessment of alternatives against a performance criterion. The meaning of scales pertaining to this study is detailed in Table 6. Step 6: Development of permanent matrices using interaction matrix and inheritance score. Step 7: Computation of permanent value of matrices using Jurkat and Ryser (1966) formula. It is computed similar to determinant by replacing all signs with positives. In general, if we expand the general form (Equation (2)) of permanent matrix,
n! (Factorial) combination of relationships exists
one loop (relationship) among inheritance score (diagonal of matrix)
As Muduli et al. (2013) states, second loop does not exist and (n1) interaction of inheritance is not possible because selfloop does not exist.
All other combinations of (n2), (n3), … (nen) relationship of inheritance exist
Zero (nen) inheritance relationship represents interaction between edges (non-diagonal element of matrix) Using ‘permanentryser ()’ function in MATLAB software package, the permanent value for five strategies are computed. Step 8: Based on the computed permanent values, SMSs was ranked. Step 9: Deployment of influential SMS: Based on ranking from permanent value computation, the important SMS are

Fig. 3. Universal digraph depicting SMMs interactions.

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Table 7 Illustration of interdependency among SMMs. S. No

Interactions

Relationship

Explanation

1. 2.

I14 I1A

Health and safety of operator (SMM1) / Economics of manufacturing process (SMM4) Health and safety of operator I14 (SMM1) 4 Social benefits (SMMA)

3.

I18

Health and safety of operator (SMM1) 4 Restricted substances content used by process (SMM8)

4.

I26

Waste intensity of process (SMM2) 4 Carbon footprint (SMM6)

5. 6. 7.

I28 I29 I2A

Waste intensity of process (SMM2) / Restricted substances content used by process (SMM8) Waste intensity of process (SMM2) / Recyclability of consumables (SMM9) Waste intensity of process (SMM2) 4 Social benefits (SMMA)

8. 9. 10. 11. 12.

I31 I36 I38 I3A I45

GhG intensity (SMM3) / Health and safety of operator (SMM1) GhG intensity (SMM3) /Carbon footprint (SMM6) GhG intensity (SMM3) 4 Restricted substances content used by process (SMM8) GhG intensity (SMM3) / Social benefits (SMMA) Manufacturing economy of process (SMM4) 4 Water footprint (SMM5)

13.

I49

Manufacturing economy of process (SMM4) 4 Recyclability of consumables (SMM9)

14. 15.

I5A I69

Water footprint (SMM5) 4 Social benefits (SMMA) Carbon footprint (SMM6) 4 Recyclability of consumables (SMM9)

16. 17. 18. 19. 20. 21. 22.

I6A I74 I76 I86 I89 I8A IA9

Carbon footprint (SMM6) / Social benefits (SMMA) Energy Intensity (SMM7) / Manufacturing economy of process (SMM4) Energy Intensity (SMM7) / Carbon footprint (SMM6) Restricted substances content used by process (SMM8) / Carbon footprint (SMM6) Restricted substances content used by process (SMM8) / Recyclability of consumables (SMM9) Restricted substances content used by process (SMM8) / Social benefits (SMMA) Social benefits (SMMA) / Recyclability of consumables (SMM9)

SMM1 complements SMM4 SMM1 and SMMA strongly enhances each other SMM8 enhances SMM1 on the other hand SMM8 is the result of SMM1 SMM6 is the result of SMM2 on the other hand SMM2 influences SMM6 SMM2 shrinks SMM8 SMM2 enhances SMM9 SMMA drives SMM2 on the other hand SMM2 complements SMMA SMM3 influences SMM1 SMM3 strongly enhances SMM6 SMM3 mutually influences SMM8 SMM3 complements SMMA SMM5 strong drives SMM4 on the other hand SMM4is the result of SMM5 SMM4 Strongly complements each other SMM9 SMM5 complements each other SMMA SMM9 confines SMM6 on the other hand SMM6 encourages SMM9 SMM6 defines SMMA SMM7 strongly determines SMM4 SMM6 is the result of SMM7 SMM8 influences SMM6 SMM8 demands SMM9 SMM8 defines SMMA SMMA demands SMM9

considered for deployment. First, the awareness about selected SMS among officials and employees is created. In the awareness meeting, the operational difficulties, benefits of SMS deployment with supporting documents (mathematical analysis and other assessment comparison with existing practice) and support required from employee are discussed. Further, the implementation plans and time horizon are also discussed. Finally, based on the initial results, comparison in terms of sustainability characteristics is debated. On satisfactory achievement of results, the deployed strategy is completely put into practice.

5. Case illustration and discussions The proposed methodology (9 steps) shown in Fig. 2 is used to assess the identified SMSs. First two steps involved in identification of SMMs and SMSs have already been detailed in the problem description section. The description of steps 3e9 are explained in this section. These help to a derive ranking of alternatives. Based on ranking, an impactful strategy is deployed. 5.1. Ranking the strategies

important steps: development of universal digraph, matrix representation with experts' score for interdependency and inheritance, and computation of permanent values.

5.1.1. Development of universal digraph (step 3) The developed universal digraph is presented in Fig. 3. As seen in Fig. 3, inheritances are represented in vertex (SMMi's) and interdependencies in links (Iij's). Totally, 31 interdependencies exist, of which 18 are mutual. The description of interaction among SMMs is presented in Table 7.

5.1.2. Matrix representation of interdependencies (steps 4e6) To represent interaction, a 10  10 matrix is configured. Then, the identified interactions are marked in non-diagonal position and ‘0’ is substituted for a position where interdependency does not exist. Based on digraph, the universal matrix configured is shown in Equation (3). This matrix computes scores for SMSs. Then, the scale shown in Table 5 is used to represent an interdependency relationship. With reference to Table 5, values for links are obtained from the team of expert and shown in Equation (4). The values shown in Table 8 replace the diagonal elements in Equation (4).

Using graph theory approach, SMSs are ranked and impactful strategy is identified. The ranking of SMSs consists of three Table 8 Experts opinion on SMSs inheritance.

SMS1 SMS2 SMS3 SMS4 SMS5

SMM1

SMM2

SMM3

SMM4

SMM5

SMM6

SMM7

SMM8

SMM9

SMMA

3 7 3 7 7

5 8 6 6 7

7 7 6 7 7

9 4 6 3 3

3 5 5 3 5

7 7 5 6 5

9 3 3 3 5

1 7 3 3 7

1 7 3 3 7

7 8 6 7 8

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2

SMS1 6 0 6 6 l31 6 6 0 6 6 0 SMSk ¼ 6 6 0 6 6 0 6 6 I81 6 4 0 IA1 2 6 6 6 6 6 6 6 SMSk ¼ 6 6 6 6 6 6 6 4

SMS1 0 3 0 0 0 0 2 0 4

0 SMS2 0 0 0 I62 0 0 I92 0 0 SMS2 0 0 0 3 0 0 3 0

0 0 SMS3 0 0 0 0 I83 0 0 0 0 SMS3 0 0 0 0 3 0 0

I14 0 0 SMS4 I54 0 I74 0 I94 0 3 0 0 SMS4 4 0 4 0 4 0

0 0 0 I45 SMS5 0 0 0 0 IA5 0 0 0 3 SMS5 0 0 0 0 2

0 I26 I36 0 0 SMS6 I76 I86 I96 0

0 0 0 0 0 0 SMS7 0 0 0

0 3 4 0 0 SMS6 3 3 3 0

0 0 0 0 0 0 SMS7 0 0 0

  PerðSMSk Þ ¼ SMSk Iij

(5)

where k ¼ 1e5 The logic of expert teams on inheritance score assignment is detailed below. As an example, employee skill training (green strategies) and involvement programs (SMS5) are detailed below. It is assumed that, in the case organization, employee involvement program and basic training on sustainable manufacturing practices are conducted. The first important aspect is health and environment safety of the operator. As already defined, human hazard is an impact factor for poor environmental image of the welding process. Thus, training on proper usage of safety equipment and masks can reduce accidents. Deployment of this strategy has higher influence on health and safety of the operator. Similarly, after discussions and collecting group knowledge, scores for other strategies are provided.

5.1.3. Computation of permanent value (step 7, 8) Using Equation (5), the permanent value for five strategies is computed. For computing permanent value, Equation (4) filled with inheritance scores of SMSs obtained from experts is used. To enable a comparison of values, a logarithm of values is computed and presented in Table 9. This unitless numerical value is the measure of importance of the strategy through which SMSs are ranked. The ranking helps to identify a SMS, most important for the SMAW process.

Table 9 Permanent scores for SMSs and its ranking. Strategy

Permanent of matrix

Log10 Rank

Energy modeling and optimization studies (SMS1) Waste minimization and disposal studies (SMS2) Process optimization (Consumables) studies (SMS3) Process emission studies (SMS4) Employee skill training (Green) and involvement program (SMS5)

227039922 513095940 106706754 117624636 563382030

19.24 20.05 18.48 18.58 20.14

3 2 5 4 1

I18 I28 I38 0 0 0 0 SMS8 0 0

0 I29 0 I49 0 I69 0 I89 SMS9 IA9

2 2 3 0 0 0 0 SMS8 0 0

0 3 0 4 0 3 0 3 SMS9 3

I1A I2A I3A 0 I5A I6A 0 I8A 0 SMSA

3 7 7 7 7 7 7 7 7 7 7 7 7 7 7 5

4 3 3 0 3 3 0 2 0 SMS10

(3)

3 7 7 7 7 7 7 7 7 7 7 7 7 7 7 5

(4)

5.2. Deployment of strategies (step 9) The ranking obtained from permanent value shows, employee skill training (green strategies) and involvement program (SMS5) as the most influential strategies. Past studies by Vimal and Vinodh (2012), Jabbour and Santos (2008) and Muduli et al. (2013) proved the importance of employee training and involvement programs in various advanced manufacturing strategies deployment. However, Clelland et al. (2000) states that minimizing waste as a first step toward implementing sustainable practices in an organization. Incidentally, waste minimization and disposal strategy is ranked second in the present study. Thus, initiatives have been taken to deploy employee skill training (green strategies) and involvement program (SMS5), and waste minimization and disposal studies. As far as employee skill training (green strategies) and involvement program (SMS5) is concerned, initiatives toward training employee on green schemes were taken. The modules covered in employee training include: team formation, sustainable manufacturing awareness program and introduction on other identified SMSs. After completion of basic training, waste minimization and disposal studies (SMS2) are deployed. As mentioned in the problem statement, stub is a major waste in the SMAW process. At present, stub is disposed of by landfill. The stub consists of 50 mm (average) of which 25 mm is covered with flux. The composition of flux is presented in Table 10. Some of the

Table 10 Percentage weights composition of flux. Chemical component

Weight composition

Calcium carbonate Fluorspar Titanium dioxide (ruttle) Potassium titanate Feldspar Potassium silicate Sodium silicate Ferro manganese Ferro silicon Iron powder

15e30% 15e30% 0e5% 0e5% 0e5% 5e10% 0e5% 2e6% 5e10% 25e40%

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minerals in the flux are active components which adversely impact the environment on disposal without processing. Also, 50 mm of core wire (average weight ¼ 3.06 g) is disposed of by landfill. The composition of core wire is presented in Table 11. By adopting alternative disposal scenario, active components can be disposed of using environmentally-friendly options. Further, for core wire, recycling can be done to conserve natural resources. The alternate disposal scenarios adopted for disposing flux include: incineration, 25% landfill þ 75% incineration and 75% landfill þ 25% landfill. Also, the selected three disposal scenarios are compared with 100% landfill scenario (current practice). On the other hand, for core wire, 100% recycling is proposed and compared with 100% landfill scenario (current practice). The proposed scenarios are compared with the current practice using a suitable environmental assessment method. In general, the approaches for environmental assessment of a product can be classified as: qualitative and quantitative approaches. Quantitative method is used when quantitative data is not available and cost of collecting it is very high (Perotto et al., 2008). The qualitative methods of assessment include: environmental performance assessment using ANP (Liu and Lai, 2009), fuzzy logic approach (Liu et al., 2009), data envelopment analysis (Zhao et al., 2006) and questionnaire based method (Canter, 1996). Hermann et al. (2007) combined LCA and MCDM techniques to compute the environmental performance of a firm with missing data. On the other hand, the quantitative method of environmental performance includes: LCA, material analysis (Worrell, 1995) and energy analysis (Gutowski et al., 2006). Material analysis and energy analysis are partial assessments considering only material flow and energy consumption during the production. On the other hand, LCA is an approach that analyses the complete life cycle stages including raw material acquisition, production process, use, and disposal of the product (Lindfors, 1995). The strengths of LCA include, long-term benefits in environmental protection, consideration of emissions of all three compartments (air, water and soil) and decision making by comparing alternative scenarios with the existing practices (Karmperis et al., 2013). Also, with the availability of inventory data, the usage of LCA is highly preferred for computing environmental burdens over other methodologies. LCA methodology outlined by ISO 14040 (2006) and ISO 14044 (2006) is adopted. LCA methodology has four steps: goal definition, inventory analysis, life cycle impact assessment and interpretation (Kasah, 2014). LCA is conducted by modelling the scenarios in SimaPro LCA package. Foolmaun and Ramjeawon (2008) recommended the modelling of EoL scenarios in SimaPro for comparison of environmental perspectives. SimaPro 7 is a LCA package used by academicians and practitioners (Herrmann and Moltesen, 2015). The package follows LCA methodology outlined by ISO 14040 (2006) and ISO 14044(2006), and can be used for characterization, damage assessment, normalization and weighting. For

Table 11 Percentage weight composition of core wire. Composition

Weight composition

Carbon Copper Manganese Silicon Sulphur Phosphorus Nickel Chromium Vanadium Molybdenum Iron

.06e.15% .50% max. 1.40e1.85% .80e1.15% .035% max .025% max .15% max. .15% max. .03% max. .15% max. Remaining %

11

characterizing the inventory data, SimPro package supports the characterization model namely: ReCiPe, Eco-Indictor, BEES, CML, EPS and others (SimaPro, 2014). The procedure followed is as follows: 5.2.1. Goal of the study Comparing the alternate disposal scenarios of stubs and core wire. 5.2.2. Inventory data Inventory data is collected for E7018 electrode of length 420 mm and diameter 3.2 mm. The composition of flux and core wire is shown in Tables 10 and 11. 5.2.3. Life cycle impact assessment For the collected inventory data, four disposal scenario for flux (including current practice) and two disposal scenario for core wire (including current practice) are formulated. Then, Eco-Indicator’99 model was adapted to characterize environmental impact scores. The computed score is shown in Fig. 4. 5.2.4. Interpretation Based on the results, 100% incineration is selected for flux and 100% recycling is chosen for core wire. Compared to existing practices (100% landfill e 7.4 environmental points, Fig. 4), 100% incineration results in 57.7% (3.3 environmental points, Fig. 4) improvement in environmental performance whereas 100% recycling results in 3.06 g/electrode of material conservation. The recycling of core wire also resulted in positive environmental impact, due to conservation of natural resources. Thus, 100% recycling for wire and 100% incineration for flux are recommended to WRI, BHEL, India. 5.3. Results and discussions The ranking of SMSs and inferences derived based on deployment of waste minimization and disposal strategies are discussed as follows. The identified five strategies are ranked using the graph theory approach. The five strategies are selected after studying the dynamics (Fig. 1) of the SMAW process. SMAW process produces waste (stub) and emits GhGs like CO, NOx, Ozone, etc. Also, the SMAW process is energy intensive, so energy efficiency can be improved by process modelling and parametric optimization. As, sustainable manufacturing is an advanced manufacturing system to which the employees have little exposure thus, basic training needs to be given to them. Thus, five strategies are formulated after discussion with the expert team. Using graph theory, SMMs interactions were modelled to calculate permanent scores. The logarithmic value for five strategies: energy modelling and optimization studies (SMS1), waste minimization and disposal studies (SMS2), process optimization (consumables) studies (SMS3), process emission studies (SMS4), employee skill training (green strategies) and involvement program (SMS5) are 19.24, 20.05, 18.48, 18.58 and 20.14 respectively. Based on this score, employee skill training (green strategies) and involvement program (SMS5) is identified as most appropriate strategy. Few authors emphasized the importance of green training while initiating sustainable manufacturing practices. Interpretive Structural Modelling model developed by Muduli et al. (2013) categorized training as a driver for green practices in mining industries. Also, Vimal and Vinodh (2013) emphasized that employee training should be an important criteria to assess sustainable manufacturing practices. On the other hand, Rashid et al. (2008) argued that, waste minimization should be the first step in implementing sustainable manufacturing practices compared to

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Fig. 4. Environmental impact scores of flux disposal scenarios.

other SMSs. Also, Foolmaun and Ramjeawon (2008) emphasized that, proper deployment of disposal scenarios has huge impact on overall environmental performance. Also, Yang et al. (2011) conducted a hypothetical test and found positive correlation between environmental performance and lean manufacturing practices. In the past, waste elimination was recognized as one of the pillars of lean manufacturing (Vinodh and Vimal, 2012). The improvement in environmental performance through implementation of waste minimization and disposal studies (SMS2) can be appreciated. Thus, both these strategies are implemented. Employee skill training (green strategies) and involvement programs (SMS5) and waste minimization and disposal studies (SMS2) are resorted to with respect to the SMAW process. In employee skill training (green strategies) and involvement program (SMS5), various modules like team formation and basic training on identified strategy are conducted as a part of employee skill training (green strategies) and involvement program strategy. The second strategy is waste minimization and disposal studies. In this, alternate disposal methods were proposed and compared to existing practice using a method outlined in ISO 14040 (2006) and ISO 14044 (2006). The results favoured 100% incineration for flux and 100% recycling for core wire as sustainable scenarios. In the present study, deployment of vital strategies is demonstrated because of economic constraint and other associated difficulties in dedicating the required human hours. But, to make SMAW a sustainable process, other SMSs also need to be implemented. In future, studies on deploying other strategies will be conducted and demonstrated. 6. Conclusions and future research directions Sustainable manufacturing has been viewed as a sole belief to cope with material scarcity, energy scarcity and to improve a green competitive advantage (Alblas et al., 2014). Also, globalization facilitates Indian manufacturers to stable their position in a global market, but government regulations and pressures to survive in global market are entirely different (Kumar, 2014; Reddy, 1997). The increased awareness of customers towards environment and uncompromising law of environmental management forces

manufacturers to adopt sustainable manufacturing practices. In the past, many studies were conducted from material and product development perspectives (Kaebernick et al., 2003). However, new economic development opens up opportunities for process sustainability improvement. Indeed, a clear methodology to improve sustainability of the manufacturing process is missing compared to a product development perspective. In this regard, a unique approach was proposed to model the interaction of SMMs, assess SMSs and deploy the latter to improve sustainability characteristics. The SMAW process was identified as the candidate process for which five SMSs were identified considering past the literature and expert analysis. Using the solution methodology, SMSs were assessed and permanent values and their logarithmic equivalents were computed. This unit less numerical value (logarithmic form) is the measure of SMSs importance which shows employee skill training (green strategies) and involvement program (SMS5) as the most vital SMS followed by waste minimization and disposal studies (SMS2). By studying dynamics of the SMAW process, the importance of waste minimization and disposal studies is appreciated (Fig. 1). For flux and core wire, new disposal scenarios are developed and through LCA methodology, alternative disposal scenarios are assessed. 100% incineration for flux and 100% recycling for core wire are identified as the best scenarios. Further, recycling of core wire earlier disposed by landfill conserves natural resources. Thus, the result of study reduces negative environmental impact as well as conserving resources. This describes the practical utility of the proposed approach and its environmental benefits in an Indian manufacturing scenario. The universal digraph developed in this study is generic and can be used for the analysis of other manufacturing processes. However, the number of indicators can be expanded considering more economic and social measures like living standards, health hazard on community etc. Also, measures using process parameters can be included to improve practical validity of the model. This work advances the existing research on sustainable manufacturing practices of the welding process. The results suggest that, deployment of SMSs improves environmental performance of the manufacturing process. Thus, deployment of SMSs forms the

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prerequisite to improve sustainable performance of the manufacturing process. The work may shift the focus of welding research from aerosol and fume analysis with regard to human health toward redesigning processes enabling sustainability in the near future. This work increases the awareness among managers to understand the interaction of manufacturing processes with the environment. A proper understanding of this may direct future research toward developing and deployment of SMSs for any manufacturing process. From a practical implications point of view, it provides systematic guidelines for managers to shift from a traditional way to a sustainable way of manufacturing with limited information. This ultimately enables sustainable operation within the firm. From a competitive (economical) advantage point of view, this study models SMMs to select the best SMS for the SMAW process which helps to achieve economic sustainability. Finally, this study helps to leverage environment, economic and social performance to achieve sustainable operations (Sueyoshi and Goto, 2010). The above discussion validates the theoretical and practical research contributions of the study. The limitation of the present work is the usage of expert opinion to assess the inheritance of SMSs. In the future, expert opinion can be replaced using the data collected based on trial studies on implementing strategies. Based on the scores of SMMs performance, further deployment can be planned. The conduct of a trial study may explore the difficulties associated with the deployment of SMSs. Also, a dedicated decision support system can be developed to support the organization which utilizes more manufacturing processes.

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