en-lean: a framework to align lean and green manufacturing in the

238 Int. J. Enterprise Network Management, Vol. 1, No. 3, 2007

Copyright © 2007 Inderscience Enterprises Ltd.

En-Lean: a framework to align lean and green manufacturing in the metal cutting supply chain

Rapinder Sawhney,* Pamuk Teparakul, Aruna Bagchi and Xueping Li Department of Industrial and Information Engineering, University of Tennessee, 416 East Stadium Hall, Knoxville, TN 39776-0700, USA Fax: +1-865-974-0588 E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] *Corresponding author

Abstract: Literature provides numerous examples of the effectiveness of Lean operations (Lean) in increasing the competitive posture of manufacturers. However, less obvious is the impact of Lean on the environmental performance of the manufacturer. A methodology is proposed that allows one to articulate the complex relationship between Lean principles and their overall environmental impacts for specific processes. A case study illustrates the application of the methodology to the metal cutting industry using single and/or multipoint cutting.

Keywords: lean manufacturing; green manufacturing; green supply chain; chip forming; metal cutting.

Reference to this paper should be made as follows: Sawhney, R., Teparakul, P., Bagchi, A. and Li, X. (2007) ‘En-Lean: a framework to align lean and green manufacturing in the metal cutting supply chain’, Int. J. Enterprise Network Management, Vol. 1, No. 3, pp.238–260.

Biographical notes: Rapinder Sawhney is an Associate Professor in the Department of Industrial and Information Engineering at the University of Tennessee-Knoxville. His research interests include manufacturing planning and control systems, lean production systems and simulation modelling.

Pamuk Teparakul is a Graduate Student in the Department of Industrial and Information Engineering at the University of Tennessee-Knoxville.

Aruna Bagchi is a Graduate Student in the Department of Industrial and Information Engineering at the University of Tennessee-Knoxville.

Xueping Li is the Director of the Intelligent Information Engineering and Systems Laboratory (IIESL) and an Assistant Professor in the Department of Industrial and Information Engineering at the University of Tennessee-Knoxville. He received an MS in Computer Science and a BS in Automatic Control from Nankai University, China. His research interests include information assurance, web mining, sensor networks, scheduling and operations research. He is a member of IEEE and INFORMS.

En-Lean: a framework to align lean and green manufacturing 239

1 Introduction

US manufacturers are under tremendous pressure to improve productivity in order to remain competitive in the global market. Over the past several decades there has been a significant shift around the globe towards Lean practices, many of which are centred on reducing waste in the manufacturing process (Ahlstrom, 1998; Feld, 2000). This strategy is credited for radically improving profitability, customer satisfaction and employee morale (Arbós, 2002; EPA, 2003; Feld, 2000; Warnecke, 1995). Manufactures are also faced with increased awareness and responsibility to the environment. These organisations focus on the environmental factor, not only because of government regulations, but also because their suppliers or customers are more environmentally demanding (Gordon, 2001). As a response many manufactures consider environmental management as an integral part of economic development and a necessity for remaining competitive (Tibor and Feldman, 1996). This focus on the environment has led to the concept of environmentally conscious manufacturing, also referred to as Green Manufacturing (Green). Green strategies have moved from being only end-of-the-pipe control to being an inherent result of process improvements. As such, it is only natural that the concept of Lean, with its inherent system view and focus on systematically eliminating waste with in-process activities, is considered a good partner in the strategy of actively protecting the environment (Byers, 1994; Chagnon et al., 1999; EPA, 2003; Lovins et al., 1999; Porter and Van Der Linde, 1995).

However, the nature of this relationship, nonetheless, remains inconclusive, as there is little to explain the conflicting findings researchers have obtained. Literature provides evidence of a positive correlation between Lean and the environment. Gordon (2001) claims that environmental management and high performance manufacturing require similar skills and resources. Therefore, plants that operate under Lean principles will have a greater ability to reduce pollution. Another study reported that manufacturers with employee participation practices had triple the reductions in Toxic Release Inventory emissions than that of other manufacturers (Bunge et al., 1996). This empowerment of workers associated with Lean practices is verified at Boeing to give rise to “greater levels of worker participation in environmental activities in Lean plants”. Lean at Boeing not only affected the energy, raw material and non-product output, but also had a positive impact on the environment (EPA, 2000).

On the other hand, researchers suggest a negative correlation between Lean and environmental performance. EPA (2000) points out that continuous improvement effort in Lean plants may be thwarted due to environmental regulatory restrictions. Regulatory restrictions can make it difficult to make environmentally sensitive processes Lean. Specifically, EPA (2000) attributes this to the inability to match one-piece flow of Lean with the batch and queue, mass production mentality of environmental regulatory systems. Also, stringent environmental regulations may require high cost pollution abatement equipment which is seen as reducing the economical productivity of the firm (Bartel and Thomas, 1987). This is another example of a mismatch between Lean and environment efforts since Lean avoids the use of non-value-added abatement equipment, which might be crucial in order to decrease emissions (Rothenberg et al., 2001). Shen (1995) suggests the emphasis of Lean on small lot production could result in more wastewater generated, as well as more energy usage due to frequent start-over.

240 R. Sawhney et al.

An analysis of the literature reveals the conflict in the literature is due to two primary reasons. Firstly, most research linking Lean with environmental metrics have narrowed their focus to single Lean principles or single environmental metrics rather than analysing multiple Lean principles over multiple measures of environmental performance. Secondly, some relationships between Lean and environment depend on various factors, which can be summarised as follows:

1 The relationship is manufacturing process specific: The reported relationship is dependent upon the type of manufacturing process under consideration. For example the environment-Lean relationship may be positive for regular processes but may be negative for environmentally sensitive processes that are highly regulated by environment agencies.

2 The reported relationships are dependent upon the subset of Lean principles that are being considered. For example small lot production might prove to be environmentally damaging. Continuous improvement and environment regulations also may not go hand in hand.

3 The relationship is environmental performance metrics specific: For example Lean is seen to have a positive impact on the reduction of toxic emissions. The reported relationships are limited in existing studies, since the measures of environmental performance considered are usually one dimensional in nature (i.e. only energy use or toxic emissions). In order to fully understand the relationship between Lean and environmental performance, one must look at a variety of environmental performance metrics.

4 The Lean-environment relationship is culture specific. For example, if water is a cheap utility and cost is the important factor of consideration, then the company might not restrict the use of water in order to maintain quality which is held as a priority as opposed to reduction in waste water generation. On the other hand, if waste water control is held as important as quality then the company will focus on reduction in waste water as well as maintain good quality.

2 Problem statement

The advantages of integrating Lean and environmental efforts are widely understood in industry. In order to exploit the advantages of efforts that integrate both, it is first necessary to understand the relationship between the two. Figure 1 brings out the fact that production and environmental inputs, both, impact the same manufacturing process. However, it is most often seen that Lean based decisions impacting the facility are made without considering the impact of the modification on environmental considerations of the facility. Similarly, environmental decisions are made without any true operations involvement. Operations personnel focus on the production dimension of the process; that of converting raw material to finished products in an efficient manner. In fact, environmental needs are generally seen as a constraint on operation strategy (Angell and Klassen, 1999). Environmental personnel, on the other hand, focus on the environmental dimension of the same process. As a result, environmental activities and Lean implementation efforts are conducted in a vacuum from each other given that both groups are impacting the same exact manufacturing process as illustrated in Figure 1 (EPA, 2003; Hanna et al., 2000).


Much needs to be understood about the relationship between a comprehensive set of Lean principles and their environmental impact. Until these relationships are understood, any expectation of cross-functional activity is unreasonable. There are few individuals in academia or industry that have the necessary expertise in both the operations and environmental details of manufacturing to bridge the current gap that exists between the two domains. Research is required to develop methodologies that lead researchers and practitioners in developing these relationships. There are two main problems in developing such methodologies as indicated in the literature. Firstly, the methodology must evaluate the impact of multiple Lean principles over multiple environmental metrics as different principles of Lean seem to affect the environment differently. Secondly, the methodology must be able to accommodate application specific input to develop the relationships.

Figure 1 The two dimensions of a manufacturing process

A methodology is presented which provides the framework to overcome these two barriers. The methodology is based on initially developing a comprehensive yet generic relationship between Lean and environmental metrics. The methodology further allows individuals to utilise this base framework as a starting point for customising the model for specific applications.

3 En-Lean methodology

Environmentally Lean (En-Lean) is a methodology to assist in developing the relationship between environmental concerns and Lean principles for specific processes. The methodology is decomposed into four distinct phases, represented in Figure 2 and discussed in detail in the following sections.

The first phase involves developing the En-Lean base matrix identifying the relationship between Lean principles and the environment. For the case study presented in this paper, a focus group consisting of Lean and environmental experts at the University of Tennessee developed the matrix to quantify the relationship between Lean principles and specific environmental factors affected by them. The second phase customises the En-Lean matrix for the specific type of process family, application or industry. This involves defining the methodology for data collection specific to Industry/Manufacturing process. The interview format and the rating system are


determined prior to determining the right sample size to ensure consistency in statistical analysis. By creating an interview checklist and choosing qualified industry specialists reliability of the data obtained is ensured. The third phase is analysing the data collected from the previous stage. Analysis is a two-fold process; the first step is to calculate the overall environmental impact score specific to each Lean principle. A sensitivity analysis reveals the most critical environmental criterion. The final phase automates the En-Lean matrix for flexibility and ease of analysis, through a specifically tailored software model. The interface provides better usability and accessibility by being built on platforms that could be used via the internet. The data and results analysed could be disseminated to the industry to modify the En-Lean for future analysis.

Figure 2 The En-Lean methodology. Four phases are involved: develop base En-Lean, collect industrial data, analyse industrial data and develop industrial interface

3.1 Phase 1: developing base En-Lean

The En-Lean matrix illustrated in Table 1 is the foundation of the methodology. It is critical to develop this matrix correctly as it will serve as the basic relationships between Lean principals and environmental metrics. This matrix serves as a foundation for any application. A focused group that included Lean experts and environmental experts at the University of Tennessee assisted in developing the matrix. Lean principles represent the vertical axis of the basic En-Lean matrix. Lean is delineated into the


following phases: planning, work place design, flow design, support function design, variation reduction and sustaining change. Lean principles utilised in this study include employee involvement and empowerment, mistake proofing, quick changeover, cellular manufacturing, pull systems, small lot production, product mix/variability, total productive maintenance and supplier development (Askin and Goldberg, 2002; EPA, 2003; Feld, 2000; Irani, 1999; Nichols, 2001; Ron, 1998; Warnecke, 1995). All the principles identified in this study are associated with phases of Lean implementation that result in process modifications impacting the environmental metrics. The four functions that focus in on process improvements and therefore impact the environmental metrics are planning, work place design, flow design and support function design. The first principle, employee involvement and empowerment, represents the planning phase of Lean implementation. Mistake proofing and cellular layout are two Lean principles that represent the workplace design phase of Lean implementation. The next four principles; pull systems, small lot production and product mix/variability represent efficient flow design. The last two principles; total productive maintenance and supplier development represent the support design phase to enable Lean within a facility. The horizontal axis of the En-Lean matrix represents common environmental metrics which include air pollution, energy usage, employee’s health and safety, hazardous waste, non-hazardous waste, special waste, universal waste, toxic chemical, wastewater and storm water runoff (EPA, 1997).

The next step in the development of the base En-Lean matrix involves identifying the specific effects of Lean principles on the environment. In order to record the impact of Lean on the environment, four levels of ratings are defined. These four levels are defined as

1 positive

2 negative

3 either positive or negative, depending on the specifics of the application and

4 no impact.

The impact of each Lean principle on the environment metrics was developed through a detailed process by the same focus group of Lean experts and environment experts. Table 2 presents a sample of the results from the focused group (cellular manufacturing impact on environmental metrics). The Lean experts delineated key characteristics of each Lean principle through case studies to explain each characteristic to the environmental experts. Based on the evaluation of the case studies and associated discussions the environmental experts subsequently identified the key environmental metrics impacted. The environmental experts next presented scenarios of the environmental impacts of the Lean principle to the Lean experts. The entire focus group results are presented in Appendix A. The summary of the results is presented in the En-Lean matrix presented in Table 1. This En-Lean matrix provides a much needed conceptual relationship between Lean principles and environmental metrics. The experts who formulated Table 1 agreed that some of these relationships could change based upon the application. However, the base En-Lean matrix is the foundation to develop customised En-Lean matrices.


Table 1 Base En-Lean


Table 2 Cellular manufacturing impact on environmental metrics

Environmental metrics

Cell manufacturing delineation

Environmental impacts Positive/negative

Air pollution Lesser exhaust Energy

Higher machine efficiency Lesser power consumption

Positive

Wastewater Fewer points of material transfer

Reduction in leaks and spills during material transfer

Hazardous waste Universal waste Special waste Non-hazardous waste Toxic chemical

Fewer points of material transfer


Positive

Storm water runoff Fewer points of outdoor material transfer

Reduction in leaks and spills during material transfer between outdoor workstations

Positive

Employee’s health Fewer points of material transfer

Less exposure to leaks and spills during material transfer

Positive

Employee’s safety Better plant layouts

Less injury risk due to shorter walking distance

Positive

3.2 Phase 2: customising En-Lean

For En-Lean to be practical, the En-Lean matrix must be customised for each specific type of process family or application. This involves actual data collection to modify the base En-Lean matrix. Although there are several data collection methods including, mail, self-administered questionnaire, telephone interview and face-to-face interview (Neuman, 1997), the recommended survey method is face-to-face interview. One of the advantages of this data collection method is that the interviewer may control the sequence of questions and use contingency questions effectively. For example, depending on the answer to a first question, the interviewer may go to another question or skip certain questions. Moreover, face-to-face interview helps ensure that the opinions of the survey respondents are their own and are not influenced by others.

An interview checklist is created for guiding the interview process in a smooth, continuous and consistent manner. The full-filter question is recommended in order to ensure that all answers are meaningful and reliable. A full-filter question is a special type of contingency question which first asks if the survey respondents have an opinion and only if the answer is yes does the respondent have to give an opinion. Apart from the type of questionnaire the rating style is also critical in this process. Likert scales are a good choice because of its simplicity and ease of use (Neuman, 1997). Each cell entry in the matrix is an integer in the range between −5 and +5. For example, an entry of +5 in the cell formed by Lean principle A and environmental attribute 1 indicates that the Lean principle A has a strong positive impact on environmental attribute 1. The advantage of this type of scoring is that a zero represents neutrality or no impact, while a negative number implies a negative impact.


There are two other issues that must be considered to ensure that the data from the interviews is valid once the interview checklist and rating method is determined. The first issue is that the individuals interviewed must be qualified. These would be individuals that have responsibility for the entire production process under consideration with responsibilities for both productivity and environmental considerations. The case study section in this paper provides greater detail on qualified respondents. The second issue is to ensure that sufficient data is collected. Each cell entry in the En-Lean matrix is the mean of all respondents for that cell. Because the data can only be collected from a portion of the true population, the deviation between the sample mean and the population mean is of particular interest. Arnold and Groeneveld (1981) proposed a method for calculating the minimum sample size (n). To ensure that the maximum deviation of the sample mean to the population mean does not exceed ‘t’ units of population standard deviation (σ). The sample size (n) can be calculated using the following equation,

2

1n

tα=

×

where n is the minimum sample size, α is the % probability that the difference between the sample mean and the population mean does not exceed tσ; t is the unit of deviation as measured by the standard deviation σ.

3.3 Phase 3: analysing the customised En-Lean

A methodology is required to analyse and interpret the data for customised En-Lean. There are two primary objectives in the analysis phase. The first objective is to establish the relationships between Lean principles and the overall impact to the environment metrics. The end result is to inform the user of the impact of each Lean principle to each environmental metric in the context of Lean implementation in industry. This allows the user to focus on specific environmental metrics and Lean principles and the nature of the relationship between the two to guide process improvement decisions and associated efforts. The nature of the relationship is defined by the impact and the significance of the impact. This creates a multiattribute problem because Lean principles have positive impact on some environmental metrics and no impact or negative impact, on others. The specific impact on each attribute may also be dependent upon the application.

The solution to this multiattribute problem is to develop the relative importance weights for each of the environmental attributes. The direct assessment approach is used in determining the weights (Canada and Sullivan, 1989). The overall environmental impact score of each Lean principle is determined by applying the weighted evaluation model. The results are presented in Figure 3. Weighted ratings are calculated by multiplying each Lean principle’s impact on each environmental attribute (Ri,j) by that environmental attribute’s relative importance weight (Wj). These products are then summed for each Lean initiative, resulting in overall environmental impact scores

( ),1

m

i i j jj

O R W=

= ×∑


where Oi is the Overall environmental impact score of Lean manufacturing principle i, Ri,j is the Rating score of impact of Lean manufacturing principle i on environmental metric j, Wj is the Relative importance weight of environmental metric j.

Figure 3 Customised En-Lean (Single and multipoint metal cutting)

From the equation it can be seen that the overall impact score of the Lean principle depends on two factors – the relative importance weight Wj of the environmental factor and the rating score Rj from the interviews. For a particular facility at a particular situation or time frame, the data obtained from the interview is a reflection of the actual relationship between the Lean principle and the environmental factor. This means that the overall environmental impact score will change with the weights assigned to the environmental factor. Intuitively this indicates that the most critical criterion is the one that has the most weight. But this can be very misleading as the response of the overall


impact score for each Lean principle to change in weights may differ to a large extent. It should be kept in mind that Wj is dynamic, as it changes from application to application. A few of the variables impacting Wj are regulations, company culture and geography. For example wastewater in Arizona may have a different level of importance as compared to Washington State.

Thus the second objective of this phase is to establish the sensitivity of the developed relationships to the importance (Wj) of each environmental metric. The process of identifying the most critical environmental factor involves sensitivity calculations using the following equations (Triantaphyllou, 2000):

{ }( )( ) ( )

, ,

, ,

, , , ,

1Sens( )min

, if

100

k i j

j i

k i j jk ik

jk ik

k i j k i jk

k

O Oa a

a a

w

δ

δ

δ δ

=′

−< >

−

′ = ×

where Sens(k) is the Sensitivity coefficient of environmental metric k, Oj is the Overall environmental impact score of lean principle j, ajk is the Impact score of lean principle j on environmental metric k, δk,i,j is the Minimum changes in the current importance weights of environmental metric k such that ranking of Lean principle i and j will be reversed, δ ´k,i j is the Minimum changes in relative terms.

Multicriteria decision making defines the most critical criterion in two ways (Triantaphyllou, 2000):

1 Whether the indication of the best top alternative changes or not. In other words – whether changing the weights of the environmental criteria changes the ranking of the best (top) Lean principle changes. For example with a weight of 20 each the top Lean alternative, measured by the highest overall positive impact is Total Productive Maintenance. Which is the environmental factor, whose change in weight changes the ranking of Total productive maintenance?

2 Whether the ranking of the alternatives change. That is, the ranking of the pair wise comparison of two Lean principles changes.

The second method is more suitable to the problem in question. The change in rankings may determine the amount of resources being assigned to the particular Lean principle in question. The analysis is discussed in more detail in the next section.

3.4 Phase 4: industry interface of En-Lean

This phase involves the development of a computer program using HTML and JavaScript codes to serve as an interface for the users of En-Lean model. The benefits of the programme are threefold. Firstly, it enhances the usability of En-Lean model by allowing the user to assign different values for the relative weights for each environmental attribute. The programme allows the user to input different values for the individual impact scores and get the corresponding overall environmental impact score.


Secondly, it eliminates human error and tedious efforts involved in manipulating the overall score. Finally, it augments the accessibility of En-Lean model by allowing the user to publish the model through the internet.

4 Case study: metal cutting

The focus group of experts chose the chip forming process that uses single-point and/or multiple-point cutting tools to illustrate the En-Lean methodology. The experts wanted to base the research on companies with 50 or more employees in East Tennessee utilising metal cutting operations. The metal cutting process is a basic process utilised in multiple industries represented within the state of Tennessee. Both single point cutting and multipoint cutting processes were considered since both the processes have similar impacts on the environment. Appendix B describes the taxonomy of the single-point and/or multiple-point cutting process.

To make the En-Lean matrix developed in this case study user-friendly, computer based technology was utilised to automate the analysis process. The En-Lean model was developed using HTML and JavaScript codes. The model can be run with Microsoft Internet Explorer or any other Internet browsers. Figure 4 displays the screenshot of the automate En-Lean model as viewed in Microsoft Internet Explorer. Because practitioners may have different priority on their environmental concern, each would have to ability to assign the relative importance weights for each environmental attribute according to their interest. The users can conveniently change the relative importance weights in the ranges of 0 to 100 by clicking in the appropriated box and typing in the desired value. The new overall environmental impact score will then be calculated after clicking any other data fields in the screen.

Figure 4 A screenshot of automated En-Lean model


4.1 Customising En-Lean: metal cutting industry

After the choice of industry was made the data collection process began. A sample size of 28 was determined to be the appropriate. Only companies known to have made substantial progress in implementing Lean principles were invited to participate in the study. Once the companies were short listed, qualified respondents were determined by contacting each company. Qualified survey respondents are defined as the individuals who possess knowledge of Lean principles or had access to data in addition to environmental issues associated with single-point and multipoint cutting operations. A request letter, for permission to interview qualified respondents was forwarded to the short listed companies. Interviews were conducted and the ratings obtained were recorded. Based on the results, the customised En-Lean matrix for single part and multiple part metal cutting was created as presented in Figure 3.

4.2 Analysing the customised En-Lean: metal cutting industry

The study described here considered each of the five environmental metrics as equally important. Therefore, all five were assigned equal relative importance weights of 100 points as illustrated in Figure 3. Thus the overall environmental impact score would range from −500 to +500. The implementation of any Lean component, whose score is −500, would have a severely negative impact on the environmental performance of the processes. On the other hand, the implementation of Lean components with the score of +500 would have a highly positive impact on the environmental performance of the processes. Lean components that received a score of zero had no impact on the environmental performance of the process. The mean impact scores that the interviews yielded are represented in the form of grades from A to E for ease of analysis and decision-making.

For the case study in this paper, the overall impact was calculated with equal weights assigned to all the environmental attributes. In this scenario, the sensitivity analysis revealed that energy usage was the most sensitive environmental attribute, followed by wastewater, employee’s health and safety, solid waste and air emission. The calculated sensitivity coefficients are also indicated in Figure 3. For the weights considered, energy usage is revealed as the most sensitive environmental factor.

The data reported by the interview process are converted to a grading scheme, detailed in Figure 3, for ease of inference. The Lean principles that show A or B grade are the ones that are naturally or significantly positive for the environment. The management should be concerned with those Lean principles that fall in the C, D or E grade as they either show a natural or significant negative impact on the environment or seem insignificant in their effects but can be made positive if efforts or resources are expended on them. The further delineation of the C (insignificant impact) category as indicated in Figure 3 helps to focus resources. The customised En-Lean thus becomes a guide in making the decision for assigning resources.

The results of the customised En-Lean matrix for metal cutting indicated that many of the Lean principles if properly implemented have a positive impact on the environmental metrics. Specifically, 7 of the 9 Lean principles received a positive overall environmental impact score. Some of the greatest opportunities to positively impact the environmental metrics are presented in mistake proofing, and employee involvement and empowerment, which received scores of 158 and 152, respectively.


These scores reflect reality. It is logical that mistake proofing provides the ability to systematically reduce errors, such as those resulting in scrap and rework, which is a positive impact to the environment. The results indicating positive environmental impact due to employee involvement and empowerment also validates the conclusion of other studies presented in the literature.

The environmental effect of cellular manufacturing in the workplace design phase and all the Lean principles in the flow design phase are, however, not as straightforward. These are principles that could cause the greatest level of concern to the environment. All of the scores for these Lean principles fall in the category of no impact to insignificant impact. Scores of no or insignificant impact might mean that the impact of these Lean principles on the environment, unlike the others, are not inherent or natural and can be influenced by factors such as the style of implementation, nature of the application or the kind of technology used. These factors are reflected in Figure 3 in the form of subratings of the insignificant or zero scores (indicated by C with a suffix). In addition, it should be noted that these principles are interrelated. For example, one of the key objectives of Lean is to create a production system that has the ability produce variable product mix on the daily basis. Product mix/variability was the only component that received the score of zero, which implied that, for the process under scrutiny, it had no impact on the environmental metrics. The ability to produce variable product mix on a daily basis implies that one produces products in smaller lot sizes. It can be seen that the only Lean principle to receive a negative overall environmental impact score is small lot production. This result also validates Shen’s (1995) results mentioned earlier. Further, it makes sense that a greater frequency of changeovers and subsequent first papers will be counter to environmental efforts. The mechanisms to enable an efficient flow in an environment of small lot production are cellular manufacturing, quick changeover and pull systems. The cluster of C’s seen in the Lean principles of cellular manufacturing, quick changeover and pull systems, in Figure 3 highlight the insignificant impact to the environment as compared to the Lean principles. Much care should be taken in the implementation of these principles, since the effect of these principles on the environment can turn negative if not handled properly.

The support design phase of Lean implementation enables the production flow design. This phase provides not only another great opportunity to positively impact the productivity of the system, but also the environmental impact of the system. Total productive maintenance received the highest overall environmental impact score of 284 indicating that proper maintenance of equipment has a significant positive impact on the environmental metrics. Logically, it makes sense that better maintained and conditioned equipment will reduce the impact to the environment. A score of 148 for supplier development showed a positive impact on the environmental metrics. The ability of suppliers to consistently provide parts within specifications reduces that impact on the production process, which in turn reduces the environmental impact.

4.3 Automated En-Lean: metal cutting industry

A computer program was developed for the metal cutting industry, which can be adapted for other industries too. Calling up default values in the programme displays the values of impact scores of this case study and automatically calculates overall scores for the present case study. This gives the user a feel for how the programme works. Different organisations may have different priorities on their environmental concern and the


interview process in their organisation might reveal different ratings. The programme allows the user to enter rating values as well as change the weights assigned to environmental attributes. The programme calculates the overall environmental impact score based on the data input.

5 Conclusions

There are conflicting conclusions in the literature for which this study presented two main reasons. Firstly, the studies reviewed in the literature were analysing a narrow cross-section of the relationship between Lean principles and environmental metrics. Secondly, the relationships must be developed for specific processes. However a base model is required as a starting point that presents the general relationships between Lean and environmental metrics. This model helps bridge the gap between the two domains of Lean and environment and helps them work in tandem. The methodology presented in this paper allows relationships to be developed for specific processes based on a base matrix. Unlike previous research, the proposed methodology takes into account multiple measures of environmental performance and Lean principles to develop a base matrix. The methodology is applied to single and multiple point chip forming processes in the metal cutting industry.

On the whole, the results proved an eye opener to the participating companies. The case study also illustrates that there are tradeoffs between Lean and environmental performance. The results also give an indication of which of the Lean principles are inherently or naturally positive or negative to the environment and which principles need to be influenced, through careful implementation, to impact the environment positively.

The model developed in this paper and its results are for a particular manufacturing process (single-point/multipoint cutting processes) and as such serves as a stepping-stone for developing the model for other processes. However, further research is also needed to develop classifications of manufacturing processes from various industries based on commonality of environmental impacts. This would allow further applications of the proposed methodology for other groups of manufacturing processes from different industries.

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Appendix A

Table A1 Environmental impact of cellular manufacturing

Environmental issue

Feature of cellular manufacturing affecting the environmental issue

Impact on environment Positive/negative

Air pollution Lesser exhaust

Energy

Higher machine efficiency Lesser power consumption

Positive

Wastewater Fewer points of material transfer


Hazardous waste

Universal waste

Special waste

Non-hazardous waste

Toxic chemical



Positive

Storm water runoff

Fewer points of outdoor material transfer

Reduction in leaks and spills during material transfer between outdoor workstations

Positive

Employee’s health


Less exposure to leaks and spills during material transfer

Positive

Employee’s safety

Better plant layouts Less injury risk due to shorter walking distance

Positive

Table A2 Environmental impact of employee’s involvement and empowerment

Environmental issue Features of employee’s involvement and empowerment affecting the environmental issue

Positive/negative

Air pollution

Wastewater

Hazardous waste

Universal waste

Special waste

Non-hazardous waste

Toxic chemical

Storm water runoff

Employee’s health

Employee’s safety

Energy

Employee’s heath

Employee’s safety

Employees contribute by offering ideas on how to reduce adverse impact of production on environment. Employees are also involved in implementation of the ideas.

OR

Employees don’t know nor care about impact on environment.

Positive/negative: the impact of this element of Lean on environment may be either positive or negative, depending on the culture of the organisation.


Table A3 Environmental impact of mistake proofing

Environmental issue Features of mistake proofing affecting the environmental issue

Impact on environment

Positive/negative

Air pollution

Wastewater

Storm water runoff

Less machine uptimes since machine is not allowed to produce defective product

Lesser pollutants and effluents

Positive

Hazardous waste

Universal waste

Special waste

Non-hazardous waste

Toxic chemical

Lesser defects Lesser wastes Positive

Employee’s health

Employee’s safety

Lesser pollutants in the factory and safer operations

Energy

Less machine uptimes since machine is not allowed to produce defective product

Less energy consumption

Positive

Table A4 Environmental impact of product mix/variability

Environmental issue Features of product mix/variability affecting the environmental issue

Positive/negative impact on environment

Air pollution Different types of setups Maybe positive or negative depending on setup

Wastewater – –

Storm water runoff – –

Hazardous waste

Universal waste

Special waste

Non-hazardous waste

Different types of setups Maybe positive or negative depending on setup

Employee’s heath – –

Employee’s safety Difficult to automate due to variety in product mix

Negative

Toxic chemical – –

Energy – –


Table A5 Environmental impact of pull systems

Environmental issue

Features of pull systems affecting the environmental issue


Positive/negative

Air pollution Less air emission Positive Wastewater

Production restricted to only absolutely necessary items, thus reducing work-in-progress reworks and scrap

Less wastewater Positive

Storm water runoff

Reduction in outdoors work-in-progress, reworks and scrap

Less runoff Positive

Hazardous waste Universal waste Special waste Non-hazardous waste Toxic chemical


Less waste Positive

Employee’s health


Less exposure to pollution

Positive

Employee’s safety

Less overproduction Lesser opportunities for unsafe conditions

Positive

Energy Less inventory Lesser load for heating and cooling

Positive

Table A6 Environmental impact of quick changeover

Environmental issue Features of quick changeover affecting the environment


Positive/negative

Air pollution – – – Wastewater Better, simpler and well

thought out set-up procedures Less waste such as spills and leaks.

Positive

Storm water runoff – – – Hazardous waste Universal waste Special waste Non-hazardous waste Toxic chemical

Better, simpler and well thought out set-up procedures

Less waste such as spills and leaks

Positive

Employee’s health Better, simpler and well thought out set-up procedures

Less exposure to wastes such as spills and leaks

Positive

Employee’s safety Shorter and simpler set-up procedures

Less risk of injury

Positive

Energy Energy efficient set-ups Energy requirement low

Positive


Table A7 Environmental impact of small lot production

Environmental issue

Features of small lot production affecting the environmental issue


Frequent deliveries/material handling

Increased automobile exhaust

Air pollution

Frequent start-ups Increased air pollutants from machinery

Negative

Wastewater More intermediate cleaning More effluents (wastewater) – in the form of sludge, residuals, solvents (from paint processes) and the like

Negative

Storm water runoff

Frequent cleaning, outdoors Effluents; solvent from paint processes

Negative

Hazardous waste

Lower scrap and rework due to smaller lots

Lesser waste Positive

Universal waste

Special waste Non-hazardous waste Toxic chemical

More sludge and residual products from frequent cutting operations

More waste Negative

Employee’s health

Frequent cleaning More exposure to toxic chemicals in cleaning solvents

Negative

Employee’s safety

– – –

Less rework Less energy use Positive Energy Frequent shutdown and start-up

More energy use Negative

Table A8 Environmental impact of supplier development

Environmental issue Positive or negative impact

Air pollution Wastewater Storm water runoff Hazardous waste Universal waste Special waste Non-hazardous waste Employee’s health Employee’s safety Toxic chemical Energy

May be positive or negative depending on materials purchased


Table A9 Environmental impact of total productive maintenance

Environmental issue

Features of total productive maintenance affecting the environment


Air pollution Lesser equipment leaks Lesser fugitive emission Positive

Wastewater More washing and cleaning More waste water Negative

Well planned activities Lesser release of waste outdoors, from cleaning indoors

Positive Storm water runoff

More runoff if equipment is outdoors

More effluent Negative

Hazardous waste

Universal waste

Higher efficiency of processes

Less unreacted materials or byproducts, hence less waste

Positive

Special waste Very few unplanned downtimes

Lesser process materials purged from production

Positive

Higher efficiency of processes

Less unreacted raw materials or by-products generated in process

Positive Non-hazardous waste

Frequent maintenance General maintenance trash such as packaging materials, plastic wraps, paper, etc.

Negative

Higher production efficiency

Less toxic chemical waste

Positive Toxic chemical

Frequent cleaning More cleaning solvent waste such as acetone, alcohol, turpentine

Negative

Employee’s safety

Well maintained equipment Reduction in possibility of adverse events such as explosion and fire

Positive

Higher efficiency of machine due to good maintenance

Low energy use Positive Energy

More maintenance procedures

More energy use Negative


Appendix B

Process taxonomy

Note: This process taxonomy is based on Integrated Manufacturing Technology Initiative, Inc. (2003). 21st Century Manufacturing Taxonomy: A Framework for Manufacturing Technology Knowledge Management, USA.

1 Single point cutting

1.1. Single point thread cutting

1.2. Turning

1.3. Facing

1.4. Boring

1.4.1. Horizontal boring

1.4.2. Jig boring

1.4.3. Lathe boring

1.4.4. Precision boring

1.4.5. Vertical boring

1.5. Shaping

1.6. Planning

1.7. Parting

1.8. Grooving

1.9. Threading

2 Multipoint cutting

2.1. Drilling

2.2. Reaming

2.3. Milling

2.3.1. Arbour milling

2.3.2. End milling

2.4. Routing

2.5. Hammer milling

2.6. Broaching

2.7. Multipoint threading

2.7.1. Tapping

2.7.2. Die threading

2.7.3. Thread milling


2.8. Filing

2.8.1. Band filing

2.8.2. Reciprocating filing

2.9. Gear cutting

2.9.1. Gear hobbing

2.9.2. Gear milling

2.10. Gear shaping

2.10.1. Band sawing

2.10.2. Circular sawing

2.10.3. Reciprocating sawing

en-lean: a framework to align lean and green manufacturing in the

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