Accepted Manuscript Integrating and Implementing Lean and Green Practices based on Proposition of Carbon-Value Efficiency Metric Ruisheng Ng, Jonathan Sze Choong Low, Bin Song PII:
S0959-6526(15)00156-0
DOI:
10.1016/j.jclepro.2015.02.043
Reference:
JCLP 5212
To appear in:
Journal of Cleaner Production
Received Date: 12 October 2014 Revised Date:
10 February 2015
Accepted Date: 16 February 2015
Please cite this article as: Ng R, Low JSC, Song B, Integrating and Implementing Lean and Green Practices based on Proposition of Carbon-Value Efficiency Metric, Journal of Cleaner Production (2015), doi: 10.1016/j.jclepro.2015.02.043. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Title: Integrating and Implementing Lean and Green Practices based on Proposition of Carbon-Value Efficiency Metric
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Authors: Ruisheng Ng1*, Jonathan Sze Choong Low1, Bin Song1 Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075
*Corresponding author. Tel.: +65 6793 1042; fax: +65 6793 8383
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Email address:
[email protected]
ABSTRACT
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Despite strong correlation between Lean and Green, companies have found it challenging to integrate and implement Lean and Green practices simultaneously especially when resources are limited. Although there are existing model, framework, and methodologies, some limitations and challenges still exist. This paper aims to overcome some of the limitations and challenges from the existing works. Specifically, one of the objectives is to propose a methodology that aims to integrate Lean and Green practices, and enables the implementation of the integrated Lean and Green practices in an easy
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and practical manner. To achieve this objective, the proposed methodology will adopt and streamline some of the approaches used in existing works. In this methodology, an easy-to-track metric called Carbon-Value Efficiency, which aims to integrate metrics derived from Lean and Green implementation, is introduced. The other key objective is to demonstrate the applicability of the
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proposed methodology using a case study of metal stamped parts production. The results show that Carbon-Value Efficiency can be improved by 36.3%, given an improvement in production lead time
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by 64.7% and a reduction in carbon footprint by 29.9%. This case study demonstrates that the proposed methodology helps to overcome the challenge in integrating and implementing Lean and Green practices, and achieve beneficial results. Future work could study other cases and explore other case specific supporting tools and techniques in order to enhance the proposed methodology.
Keywords: Carbon-Value Efficiency, Lean, carbon footprint, value stream map, overall equipment effectiveness
9,084 words
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Integrating and Implementing Lean and Green Practices based on Proposition of Carbon-Value Efficiency Metric Ruisheng Ng1*, Jonathan Sze Choong Low1, Bin Song1 Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075
*Corresponding author. Tel.: +65 6793 1042; fax: +65 6793 8383 Email address:
[email protected]
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ABSTRACT
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Despite strong correlation between Lean and Green, companies have found it challenging to integrate and implement Lean and Green practices simultaneously especially when resources are limited.
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Although there are existing model, framework, and methodologies, some limitations and challenges still exist. This paper aims to overcome some of the limitations and challenges from the existing works. Specifically, one of the objectives is to propose a methodology that aims to integrate Lean and Green practices, and enables the implementation of the integrated Lean and Green practices in an easy and practical manner. To achieve this objective, the proposed methodology will adopt and streamline some of the approaches used in existing works. In this methodology, an easy-to-track metric called
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Carbon-Value Efficiency, which aims to integrate metrics derived from Lean and Green implementation, is introduced. The other key objective is to demonstrate the applicability of the proposed methodology using a case study of metal stamped parts production. The results show that Carbon-Value Efficiency can be improved by 36.3%, given an improvement in production lead time
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by 64.7% and a reduction in carbon footprint by 29.9%. This case study demonstrates that the proposed methodology helps to overcome the challenge in integrating and implementing Lean and Green practices, and achieve beneficial results. Future work could study other cases and explore other
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case specific supporting tools and techniques in order to enhance the proposed methodology.
Keywords: Carbon-Value Efficiency, Lean, carbon footprint, value stream map, overall equipment effectiveness
1. Introduction 1.1 Lean and Green Lean and Green often go hand-in-hand as being Lean implies reducing waste and is therefore, likely to improve resource efficiency and reduce environmental impact. This relationship is 1
ACCEPTED MANUSCRIPT evident in academic literature (Bergmiller and Mccright, 2009; Carvalho and Cruz-Machado, 2009; Dües et al., 2013; Franchetti et al., 2009; Hajmohammad et al., 2013; Hanson et al., 2004; King and Lenox, 2001; Kleindorfer et al., 2005; Larson and Greenwood, 2004; Martínez-Jurado and Moyano-Fuentes, 2013). In particular, some researchers highlighted that companies that are Lean may easily become Green companies. For instance, King & Lenox
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(2001) explain Green as the positive side-effect or good public spillover of Lean when efforts are made towards reducing waste. Likewise, Franchetti et al. (2009) also support the argument by expressing that Green manufacturing is a natural extension of Lean manufacturing. Further to that, there are several authors (Bergmiller and Mccright, 2009;
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Carvalho and Cruz-Machado, 2009; Larson and Greenwood, 2004), who point out that Lean and Green create synergy besides achieving their fundamental objectives. In particular, Larson & Greenwood (2004) describe Lean and Green as having more than just amicable co-
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existential relationship. The combination of Lean and Green could yield greater benefits than just being Lean or Green (Carvalho and Cruz-Machado, 2009). Specifically, Bergmiller & McCright (2009) provide empirical evidence that companies which incorporate both Lean manufacturing and Green manufacturing have achieved better results than companies which only focus on Lean manufacturing. This finding is in agreement with other authors (Hanson
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et al., 2004; Kleindorfer et al., 2005), who note the strong correlation between a company’s performance and the marriage of Lean and Green. In one of the most recent extensive literature review on the relationship between Lean and Green, Dües et al. (2013) compare the two paradigms, and identify their differences and overlapping relationship (Fig. 1). In this
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overlapping relationship, the following attributes are found to be common: “waste and waste reduction techniques”, “people and organisation”, “lead time reduction”, “supply chain
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relationship”, “Key Performance Indicator (KPI): service level”, and “tools and practices”. They conclude that the commonalities serve as a basis for Lean and Green implementation. Specifically, their research findings point out that a Lean environment act as a catalyst to enable Green implementation. In addition, the integration of Lean and Green will lead to better performances and results for companies.
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Source: Adapted from (Dües et al., 2013)
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Fig. 1. Overlapping relationship between Lean and Green Paradigms.
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1.2 Model, framework and methodologies
Several researchers have proposed model, framework and methodologies to integrate and implement Lean and Green. These model, framework and methodologies usually share some commonalities. They begin by assessing the current state of the value stream before
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evaluating possible tools and techniques to improve and develop future state of the value stream. These tools and techniques are primarily Lean tools and techniques such as 5S,
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Heijunka, Kaizen, Kanban, Overall Equipment Effectiveness (OEE), Poka-Yoke, Root Cause Analysis, Single Minute Exchange of Die (SMED), Takt Time, Value Stream Map (VSM), etc. The application of these tools and techniques are initially intended to improve the Leanness. Inevitably, the reduction of waste streams by being Lean will indirectly lead to improvement in Green (Franchetti et al., 2009; King and Lenox, 2001). The following section discusses some of the recent works in detail.
Pampanelli et al. (2014) propose a model which integrates Lean and Green approaches for application at manufacturing cell level. The model consists of the following five steps: •
Step 1 – Stabilise the value stream 3
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Step 2 – Identify environmental aspects and impacts
•
Step 3 – Measure environmental value streams
•
Step 4 – Improve environmental value streams
•
Step 5 – Continuous improvement
The first step is to identify an operational cell that is resource-intensive, has a good
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deployment of Lean tools, and has a production flow which is stable. These are the necessary pre-requisites to justify the application of Lean and Green model. Step 2 defines the areas for environmental improvement by identifying the relevant environmental aspects and impacts according to ISO 14001:2004. Step 3 identifies and collects data for measuring the
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environmental flows such as energy, water, metallic and contaminated waste and other waste, oils and chemicals, and effluents. Step 4 aims to identify waste elimination areas by conducting Kaizen workshops. This requires heavy involvement from the group which
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include leaders and managers, cell operators, maintenance people, and environmental and lean specialists. Lastly, step 5 develops action and communication plan for continuous improvement.
Verrier et al. (2014) analyses the practices of 21 Alsatian industrial companies using a case
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study research methodology. From the analysis, they propose a framework for Lean and Green management. The framework consists of Lean indicators, Green performance indicators and Green intentions indicators. These indicators allow comparison between companies so as to identify the best in class and respective best practices. This enables
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practices.
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company which aspire to improve its Lean and Green performance to adopt the best
To improve the Lean and Green performance, several researchers have developed methodologies which rely on a popular Lean tool known as Value Stream Map (VSM). VSM is popular and widely adopted in Lean manufacturing because it enables the visualisation of essential resource flows and waste hotspots (Abdulmalek and Rajgopal, 2007; Belokar et al., 2012; Braglia et al., 2006; Chen et al., 2010; Lian and Van Landeghem, 2007; Lu et al., 2011; Serrano et al., 2008; Singh et al., 2011). Therefore, some researchers have attempted to combine VSM with environmental metrics for visualising environmental flows. For example, Marimin et al. (2014) develop a variant of VSM which combines environmental mapping. In their research, they introduce Green Value Stream (GVS) mapping which places boxes
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ACCEPTED MANUSCRIPT containing environmental information under VSM. Their purpose is to evaluate the Green Productivity Index (GPI) which encompasses environmental and economic considerations. Besides environmental considerations, Brown et al. (2014) and Faulkner & Badurdeen (2014) add both economic and social dimensions to cover the triple-bottom line aspects of sustainability. In their work, they name the combination of sustainability and VSM as
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Sustainability-VSM (Sus-VSM). The visualisation of economic, social, and environmental dimensions in the VSM enables a holistic overview of sustainability performance in the operations. The method developed by Kurdve et al. (2014), known as waste flow mapping (WFM), combines Lean tools such as VSM with cleaner production and material flow cost
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accounting strategies. Their aim is to identify opportunities to reduce waste and material losses.
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1.3 Limitations and challenges
Despite the promising results shown by combining Lean and Green, Dües et al. (2013) also note the challenges faced by companies in the integration and implementation of Lean and Green practices. One such challenge is how to implement both Lean and Green practices simultaneously given a resource constraint situation. In other words, practitioners find it
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overwhelming and impractical to implement both Lean and Green practices with limited resources. As observed in the Sus-VSM proposed by Brown et al. (2014) and Faulkner & Badurdeen (2014), it is obviously desirable to include a multitude of considerations. Although this enables the practitioners to make informed decisions in improving the overall
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sustainability, the challenge here is the collection of vast amount of data related to sustainability. In addition, significant resources are required to map and analyse the overall
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sustainability performance. This implies that the Sus-VSM is more applicable in companies whose management are willing to spend significant resources to map and analyse the sustainability performance of the operations. Unfortunately, in companies whereby resource constraint is an issue, the applicability of Sus-VSM may be challenging. Likewise, the methodology by Marimin et al. (2014) requires additional amount of effort to collect economic data other than environmental data. Although the method developed by Kurdve et al. (2014) seems to require less resource, it has a specific focus on material efficiency and waste management. In addition, Kurdve et al. (2014) highlight that the method need further developmental work such as including the considerations for logistic inefficiencies, root cause analysis, guidelines to implement best practice, and systems to monitor performance of actors. 5
ACCEPTED MANUSCRIPT The framework proposed by Verrier et al. (2014) enables a company which aspire to improve its Lean and Green performance to adopt the best practices. However, the framework is more appropriate and applicable if there is a consortium of companies available for benchmarking. While the model proposed by Pampanelli et al. (2014) fulfils the need of an individual
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company aiming to integrate and implement Lean and Green practices, they pointed out certain limitations. For example, the current model is limited to a manufacturing cell level and future work is required to prove that the model is expandable to factory and supply chain levels. Furthermore, there are six pre-requisites for applying the model: (1) stable process
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with delivery records over 90%, (2) sufficient deployment level of lean tools, (3) employment involvement systems in place, (4) management who are supportive, (5) sense of environmental awareness, and (6) processes which use significant natural resources. These
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pre-requisites thus limit the applicability of the model to a certain extent. 1.4 Objectives
This paper aims to overcome some of the limitations and challenges from the existing works. Specifically, one of the objectives is to propose a methodology that aims to integrate Lean
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and Green practices, and enables the implementation of the integrated Lean and Green practices in an easy and practical manner. To achieve this objective, the proposed methodology will adopt and streamline some of the approaches used in existing works. The other key objective is to demonstrate the applicability of the proposed methodology using a
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case study of metal stamped parts production.
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ACCEPTED MANUSCRIPT 2. Methodology
• Analyse areas for Lean and Green improvement • Create future state Value Stream Map
Step 3: Kaizen events
Step 4: Action plans
• Identify Kaizen events for continuous improvement • Mark Kaizen lightning burst on CVE-VSM
• Develop Action Plan to document the recommendations, goals, timeline, review date, and people in charge
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• Outline product and customer requirements • Investigate production management, working time, process information, inventory, and resource flows • Monitor efficiency of manufacturing process • Create current state Value Stream Map
Step 2: Future state analysis
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Step 1: Current state assessment
Supporting tools and techniques
Supporting tools and techniques
• Overall Equipment Effectiveness (OEE) • Carbon-Value Efficiency (CVE) • Carbon-Value Efficiency Value Stream Map (CVE-VSM)
• Eight guiding questions • Carbon-Value Efficiency Value Stream Map (CVE-VSM) • Lean tools and techniques that are case and context specific according to outcome of eight guiding questions
• Tools and techniques are case and context specific according to Kaizen events
Supporting tools and techniques
• Table of Action Plan
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Supporting tools and techniques
Fig. 2. Proposed methodology which integrate and implement Lean and Green practices.
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To enable the practical implementation of integrated Lean and Green practices, the proposed methodology consists of four major steps as shown in Fig. 2. Step 1 assesses the Lean and Green performance based on the current state value streams of the production environment. Thereafter, Step 2 analyses possible areas for Lean and Green improvement so as to achieve
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the desirable outcome in future state. Having identified the specific issues and implementable initiatives, there will be critical areas where improvements are required. These areas are
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known as Kaizen events in Step 3. To realise these improvement areas, an Action Plan will need to be developed in Step 4. For each step, there are supporting tools and techniques (Fig. 2). Similar to existing works (Brown et al., 2014; Faulkner and Badurdeen, 2014; Kurdve et al., 2014; Marimin et al., 2014), tools and techniques include metrics which are necessary to measure Lean and Green performance. Specifically, Brown et al. (2014) suggest that instead of having a full set of industry-specific metrics, it is better to focus on a smaller and widely applicable set of metrics. Therefore, in this proposed methodology, one metric is introduced to streamline Lean and Green metrics. This metric is called the Carbon-Value Efficiency (CVE), which provides an indicator to evaluate Lean and Green performance by integrating metrics derived from Lean and Green implementation. It tracks value added time, a widely
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ACCEPTED MANUSCRIPT applicable metric derived from Lean implementation; as well as carbon footprint, which is also a widely known metric from Green implementation. The general concept of CVE is to track the amount of value added time created per unit of carbon footprint. It gives an indication of the proportion of the value adding activities per environmental impact, i.e. the higher the CVE value, the better. This ratio is similar to the concept of eco-efficiency
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(Huppes and Ishikawa, 2005; Ng et al., 2014a; WBCSD, 2000a, 2000b), which is creating more value with lesser environmental impacts. Likewise, the introduction of CVE is to enable operations to strive for greater value creation without compromising environmental performance. The following sections will describe the metric as well as the methodology in
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detail. 2.1 Step 1 - current state assessment
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The current state assessment involves outlining the product and customer requirements. This step also investigates the production management, working time, process information, inventory, and resource flows. The collected information is used to analyse the performance of the current state. For our work here, the Overall Equipment Effectiveness (OEE), a widely adopted and proven metric is used to monitor the efficiency of the manufacturing process
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(Ahuja and Khamba, 2008; Anvari et al., 2011; Gibbons and Burgess, 2010; Pintelon and Muchiri, 2008; Wilson, 2009).
OEE is broken down into three separate but measurable metrics of Availability, Performance,
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and Quality. The Availability metric represents the availability of the operation as a percentage of scheduled time. It measures the uptime and is calculated by dividing Run Time
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by Total Time. The Performance metric represents the speed at which the operation runs as a percentage of its designed speed. It is computed by dividing Total Count by Target Counter. The Quality metric represents the number of good parts that are produced as a percentage of the total parts produced. It is calculated by dividing Good Count by Total Count. By multiplying all the three metrics of Availability, Performance, and Quality, the OEE for individual process can be derived. Table 1 illustrates how OEE is computed using a hypothetical case.
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ACCEPTED MANUSCRIPT Table 1. Process information required for computation of overall equipment effectiveness.
Process 1 1
Process 2 1
Shift Length (min)
510
510
Meals and Breaks (min)
90
90
Changeover Time (C/O) (min)
45
9
Down Time (min) Run Time (min) = Shift Length - Meals and Breaks - Changeover Time - Down Time Total Time (min) = Changeover Time + Down Time + Run Time
13
10
362
401
420
420
1
56
Number of Operator
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Cycle Time (C/T) (s)
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Process
Target Counter (parts) = Total Time / Cycle Time
450
5.0
4.9
23,940
428
3.6
3.3
Good Count (parts) = Total Count x (1 - Defective Rate)
23,078
414
Availability (%)
86.19
95.48
Performance (%)
95.00
95.11
Quality (%)
96.40
96.73
78.93
87.84
Performance Loss Rate (%)
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25,200
Total Count (parts) = Target Counter x (1 - Performance Loss Rate)
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Defective Rate (%)
Overall Equipment Effectiveness (OEE) (%)
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Note: Hypothetical values are populated in this table to illustrate the calculation.
Besides the OEE, the collected information can be analysed and mapped into a Value Stream
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Map (VSM). The proposed methodology adopts VSM as the base tool since it is a widely adopted and popular tool for Lean and Green implementation (Brown et al., 2014; Faulkner and Badurdeen, 2014; Kurdve et al., 2014; Marimin et al., 2014). In this paper, the VSM is overlaid with an environmental metric, i.e. carbon footprint. Carbon footprint is an important metric that represents essential elements of sustainable manufacturing such as materials, energy, and waste treatment (Ng et al., 2012). According to de facto standards for carbon footprint quantification (International Organisation for Standardisation, 2013, 2006a, 2006b; The British Standards Institution, 2011), material and waste impacts include the type of materials used by the products and manufacturing processes, the material waste generated at the end-of-life of products, and their associated waste treatment process. Energy impact 9
ACCEPTED MANUSCRIPT covers the embodied energy in the materials and the consumption during manufacturing, transportation, and other related activities (Ng et al., 2012). Thus, carbon footprint would be a holistic and suitable metric to act as proxy for environmental impact. By overlaying carbon footprint on the conventional VSM, it provides users with valuable resource flows and environmental impact information. Furthermore, insights can be derived by analysing the
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ratio of value added time to carbon footprint. This ratio as measured by the Carbon-Value Efficiency (CVE) is shown in Eq. (1). CVE gives an indication of the proportion of value adding activities per environmental impact. Obviously, it is better to have a higher CVE value or a higher value added time to carbon footprint.
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VAT CFP Total
Where: CVE is the Carbon-Value Efficiency VAT is the value added time CFPTotal is the total carbon footprint
(1)
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CVE =
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To quantify the total carbon footprint, the carbon footprint generated during value added time and non-value added time must be assessed and aggregated. The formula to compute total carbon footprint can be expressed in Eq. (2).
(2)
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CFP Total = CFP VAT + CFP NVAT Where:
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CFPVAT is the carbon footprint generated during value added time CFPNVAT is the carbon footprint generated during non-value added time There are a number of methodologies to quantify carbon footprint (International Organisation for Standardisation, 2013, 2006a, 2006b; The British Standards Institution, 2011). To streamline the carbon footprint quantification, a generic formula is adopted from (Ng et al., 2014b, 2014c, 2012, 2011). Eq. (3) computes the carbon footprint generated during value added time. N
CFPVAT = ∑ (ADVAT, i × EFi )
(3)
i
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ACCEPTED MANUSCRIPT Where: CFPVAT is the carbon footprint generated during value added time ADVAT,i is the activity data during value added time for activity i EFi is the emission factor for activity i
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N is the total number of activity during value added time
Similar to assessing the carbon footprint generated during value added time, Eq. (4) computes the carbon footprint generated during non-value added time. N
(4)
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CFPNVAT = ∑ ( AD NVAT , i × EFi ) i
Where:
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CFPNVAT is the Carbon Footprint generated during non-value added time ADNVAT,i is Activity Data during non-value added time for activity i EFi is Emission Factor for activity i
N is the total number of activity during non-value added time
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The CVE proposed above and the other information are then presented in a Carbon-Value Efficiency VSM (CVE-VSM). This enables users to visualise and analyse the value adding activities based on the amount of carbon footprint generated. The CVE-VSM will be presented in the case study in the subsequent sections.
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2.2 Step 2 - future state analysis
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Having generated the current state CVE-VSM, the future state CVE-VSM is proposed based on Lean principles and techniques. For implementing Lean manufacturing, Rother & Shook (1999) outlines the following eight guiding questions to be answered: 1. What is the takt time? 2. Should company build a finished good supermarket or ship directly to customer?
3. Where is it possible to use continuous flow processing? 4. Where to use supermarket pull systems? 5. Where is the pacemaker? 6. What is the incremental work to be released and taken away at the pacemaker? 7. How to level production mix at the pacemaker?
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ACCEPTED MANUSCRIPT 8. What are the necessary process improvements?
Based on the above guidelines, Lean principles and techniques are applied to improve the CVE. Thereafter, the proposed implementable initiatives are presented in a future state CVEVSM.
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2.3 Step 3 – kaizen events
‘Kaizen’ is a Japanese term for continuous improvement (Imai, 1986). Having identified the specific issues and implementable initiatives, there will be areas where improvements are
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critical to achieve the vision of the future state CVE-VSM. These areas are marked as kaizen events with “kaizen lightning burst” (Rother and Shook, 1999). The kaizen events are case and context specific. This implies that there is no one-size-fits-all technique, and different
presented in the case study section. 2.4 Step 4 – action plans
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Lean approaches and techniques are employed on a case-by-case basis. More details will be
The current state CVE-VSM provides an overview of the existing operations and identifies
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some key issues. To overcome these issues, recommendations are proposed and captured in the future state CVE-VSM. However, the future state CVE-VSM is only a snapshot of the 'desired' status. To achieve the future state CVE-VSM, an Action Plan needs to be in place
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(Table 2).
The Action Plan details the proposed recommendations that address the issues, the goals to be
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achieved, the timeline for implementation, the review date, and the people who are responsible for implementing the recommendations. It is a 'living' document, which means it should be constantly reviewed and updated if necessary. After all, things may change due to external events, such as a change in customer requirements. However, this does not mean that the Action Plan can be taken lightly. It is similar to a 'binding' contract between the implementers and the management, and a commitment towards achieving continuous improvement.
Table 2. Example of an Action Plan to document the proposed recommendations that address the issues, the goals to be achieved, the timeline for implementation, the review date, and the people who are responsible for implementing the recommendations.
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Recommendations
Goal
Timeline
Review Date
Responsibilities
Overproduction resulting in large inventories
Implement supermarket pull system and Kanban system
To produce only what is needed and reduce large inventories
90 days
Every 30 days
•
Large delivery of raw material by supplier resulting in large inventories
Implement daily order and daily delivery of raw material in small batches
To order only what is needed and reduce large inventories
30 days
3
…
…
…
…
4
…
…
…
…
1
•
Every 15 days
Production Manager Procurement
•
…
…
…
…
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2
•
Production Manager Operators
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S/N
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5 … … … … … … Note: Hypothetical values are populated in this table to illustrate the content of an Action Plan.
3. Case study of metal stamped parts
A case study of metal stamped parts is presented here to illustrate how the proposed methodology improves the Carbon-Value Efficiency (CVE) of the production plant. Due to confidentiality of information, some data and scenarios have been desensitised and modified.
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For instance, a fictitious name, MetalTech is used to represent the company. However, the desensitised and modified information will not have any bearing on the illustration of the proposed methodology to improve the CVE of the production plant.
Product description and customer requirement
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3.1.1
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3.1 Step 1 - current state assessment
MetalTech produces metal stamped parts (MSPs). Typically, the daily customer demand is 800 MSPs. The part dimensions and the material type are shown in Table 3.
Table 3. Part dimensions and material type of the metal stamped part.
Part name Metal stamped part (MSP) Source: MetalTech
Thickness (mm) 0.5
Part weight (g) 51.9
Material Type Stainless steel
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Production management
The production management department manages the production schedule. It receives weekly order and monthly forecast from the customers. Based on this information, it sends weekly order and monthly forecast to the raw material supplier. The production management department issues weekly schedule to the operating processes and daily shipping schedule to
3.1.3
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the shipping department. Working time and process overview
There are 20 working days in a month with two available shifts per day. Each shift has 8.5
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hours including meals and breaks. After deducting 1 hour for meal and 0.5 hour of break per
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shift, the total available working hours is 7 per shift or 14 per day.
There are five main sequential processes involved in manufacturing the MSP. Firstly, the stainless steel sheets are fed into the stamping machine to be stamped out to the near-net shape part. Secondly, the part is deburred to smooth the edges. Thirdly, the part is coated with a layer of surface-coating. Fourthly, the coated part is cured before it is sent to the assembly
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process. Table 4 lists the process information.
Table 4. Process information of manufacturing the metal stamped part.
Process Number of Operator
Stamping 1
Deburring Coating Curing 1 1 1
Assembly 1
510
510
510
510
510
Meals and Breaks (min)
90
90
90
90
90
Changeover Time (C/O) (min)
45
9
7
8
8
Down Time (min) Run Time (min) = Shift Length - Meals and Breaks Changeover Time - Down Time Total Time (min) = Changeover Time + Down Time + Run Time Cycle Time (C/T) (s)
13
10
11
12
10
362
401
402
400
402
420
420
420
420
420
1
56
62
71
58
25,200
450
406
355
434
5.0
4.9
4.8
4.6
4.8
23,940
428
387
339
413
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Shift Length (min)
Target Counter (parts) = Total Time / Cycle Time Performance Loss Rate (%) Total Count (parts) = Target Counter x (1 - Performance Loss Rate)
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3.3
3.3
3.4
2.8
23,078
414
374
327
401
Defective Rate (%) Good Count (parts) = Total Count x (1 - Defective Rate) Source: MetalTech
Based on the above information, the Overall Equipment Effectiveness (OEE) can be derived.
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The calculated metrics of Availability, Performance, Quality and OEE of the processes are illustrated in Fig. 3. It can be observed that stamping process has the lowest OEE metric of 78.93%, whereas the other processes have higher and similar OEEs of around 87.73% to 88.44%. Specifically, stamping also has the lowest Availability metric (86.19%) which leads
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to the lowest OEE metric. A check against Table 4 reveals that the stamping process has relatively longer Changeover Time (45 minutes), resulting in the lowest Availability metric.
low OEE metric.
Performance
Availability 90%
95.71%
95.48%
100%
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Thus, it can be inferred that long Changeover Time is causing the stamping process to have a
95.24%
86.19%
95.71%
100%
95.00%
95.11%
95.32%
95.49%
95.16%
Stamping
Deburring
Coating
Curing
Assembly
90% 80%
80%
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70% 60%
Curing
Assembly
EP
50%
Stamping
Deburring
96.40%
96.73%
Coating
97.09%
70% 60% 50%
OEE
Quality 100% 90%
70% 60% 50%
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80%
96.64%
Stamping
Deburring
Coating
96.46%
100% 90% 80%
87.84%
88.17%
87.73%
88.44%
Deburring
Coating
Curing
Assembly
78.93%
70% 60% 50%
Curing
Stamping
Assembly
Fig. 3. Availability, Performance, Quality and OEE metrics of the processes from manufacturing the metal stamped part.
3.1.4
Large inventory
MetalTech's production follows a ‘push’ system where goods are manufactured in anticipation of customer demand. MetalTech has a typical mass production mind-set where
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ACCEPTED MANUSCRIPT each process tries to produce to its maximum capacity. Consequently, each process has piled up large inventories prior to the next process. The observed inventories between processes are summarised in Table 5. For instance, the observed inventories for MSP are 3600. By dividing total number of parts (3,600) with the daily customer demand (800), the lead time is derived to be 4.5 days. In addition, there is also a large inventory (4 days) of raw material from the
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supplier.
Table 5. Observed inventories between processes of manufacturing the metal stamped part.
Functional unit and system boundary
Deburring 2,400 3
Coating 1,600 2
Curing 1,200 1.5
Assembly 1,600 2
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3.1.5
Stamping 3,600 4.5
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Process Observed inventory Lead time (Number of days) Source: MetalTech
In this study, the functional unit is the production of one unit of MSP. As the goal of this study is to allow the management to improve the CVE, the system boundary focuses only on internal production processes and hence, covers from cradle-to-gate. Activity data and emission factors
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3.1.6
To quantify the carbon footprint, the activity data and emission factors are collected. The activity data for the MSP consists of the material type and quantity, the transport load (materials) and the distance covered by the vehicle, the energy type and consumption for the
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processes, as well as energy type and consumption of the manufacturing facilities which
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include air-conditioning and lightings. These data are listed in Table 6.
The emission factors are based on the material type as well as the transport vehicle. These emission factors are obtained from Life Cycle Assessment databases like ecoinvent (Swiss Centre for Life Cycle Inventory, 2015) and GaBi (PE International, n.d.). For the energy emission factor, it is obtained from Singapore’s electricity grid emission factor (National Environmental Agency, 2013). The Singapore’s electricity grid emission factor is the carbon dioxide equivalent value derived by summing the weighted amount of carbon dioxide and upstream fugitive methane emissions. The weighted amount is based on the global warming potential for a time horizon of 100-year as indicated in IPCC Fourth Assessment Report (Pachauri and Reisinger, 2007). These data are listed in Table 7.
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Table 6. Activity data for one unit of metal stamped part.
Prior Deburring
Deburring
Prior Coating
0.052
0.039
Prior Curing
Curing
Prior Assembly
Assembly
Prior Delivery
2.748
2.438
2.245
2.438
Curing
Prior Assembly
Assembly
Prior Delivery
0.553
0.553
0.553
6.667E-4
0.008 2.438
Coating
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Stamping
2.552E-4 2.438
2.168
0.023 2.438
1.362
2.400
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Material (kg) Energy for process (kWh) Energy for facilities (kWh) Transport (kgkm)
Prior Stamping
2.438
2.467
0.012
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Process
Note: Values are rounded to three decimal places. Source: MetalTech
Table 7. Emission factor for one unit of metal stamped part.
Prior Deburring
4.987 0.553
0.553
0.553
1.195E-4
Deburring
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Stamping
Prior Coating
0.553
0.553
Coating
Prior Curing
1.65
0.553
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Material (kg CO2e/kg) Energy for process (kg CO2e /kWh) Energy for facilities (kg CO2e /kWh) Transport (kg CO2e /kg-km)
Prior Stamping
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Process
0.553
0.553
0.553
0.553
0.553
0.553
1.195E-4
Note: Values are rounded to three decimal places. Carbon footprint is expressed in weight of carbon dioxide equivalent, e.g. kg CO2e. Source: (National Environmental Agency, 2013; PE International, n.d.; Swiss Centre for Life Cycle Inventory, 2015)
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ACCEPTED MANUSCRIPT 3.1.7
Current state CVE-VSM
A current state CVE-VSM of MetalTech which captures the above information is shown in Fig. 4. From the VSM, it can be observed that the production lead time or non-value added time (NVAT) is 17 days or 856,800 seconds but the value added time (VAT) is only 248
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seconds. The ratio of VAT/NVAT is 0.029%. Looking at the CFP metrics, the CFPTotal is 15.047 kg CO2e where CFPVAT and CFPNVAT are 6.953 kg CO2e and 8.094 kg CO2e respectively. Consequently, the CVE is calculated to be 16.482 s/kg CO2e. A summary of
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performance metrics for the current state is listed in Table 8.
Table 8. Performance metrics of current state from manufacturing the metal stamped part.
Unit s s % kg CO2e kg CO2e kg CO2e s/kg CO2e
Value 248 856,800 0.029 6.953 8.094 15.047 16.482
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Metric Value added time (VAT) Non-value added time (NVAT) ratio of value added time and non-value added time (VAT/NVAT) Carbon footprint generated during value added time (CFPVAT) Carbon footprint generated during non-value added time (CFPNVAT) Total carbon footprint (CFPTotal) Carbon-Value Efficiency (CVE)
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Fig. 4. Current state CVE-VSM of manufacturing the metal stamped part.
ACCEPTED MANUSCRIPT 3.2 Step 2 - future state analysis The current state CVE-VSM has clearly highlighted several areas for waste reduction, such as overproduction and inventory. By reducing the inventory waste, there is possibility of reducing CFP and thereby improving CVE. To determine the future state CVE-VSM, there are eight questions to be answered as described earlier in section 2.2. This will be addressed
3.2.1
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in the following sections. What is the takt time?
Takt time measures the amount of time between the completions of two consecutive units in
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order to meet customer demand (Rother and Shook, 1999). This is computed by dividing the available working time by customer demand. The daily customer demand is 800 MSPs.
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Referring to the calculation shown in Fig. 5, the takt time for each MSP is 63 seconds. This implies that to meet customer demand, MetalTech needs to produce one MSP every 63 seconds.
Takt time =
Customer demand
14 hours/day
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=
Available work time
=
800 parts
50,400 s
800 parts
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= 63 s/part
Fig. 5. Takt time calculation for each metal stamped part.
Should company build a finished good supermarket or ship directly to customer?
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3.2.2
‘Kanban’ is a Japanese term which refers to a visual signboard for signalling the initiation of work (Gross and McInnis, 2003). Since MetalTech’s customer buys in multiples of 50 parts, this will be the recommended production ‘kanban size’. Whenever the shipping department withdraws bins of 50 parts, the production kanban will be sent back to the production line which serves as a signal to produce another 50 parts. As batching is necessary at the final process, a finished good supermarket is proposed to hold inventory.
ACCEPTED MANUSCRIPT 3.2.3
Where is it possible to use continuous flow processing?
To introduce continuous flow processing, it is more appropriate to select process with similar cycle time. Observing Fig. 6, the stamping process has a very short cycle time (1 second) relative to the deburring, coating, curing, and assembly processes. Hence, it is not practical to slow down the stamping process to match the other four processes. Conversely, the other four
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processes have closer cycle time as well as being near the takt time. This means that the deburring, coating, curing, and assembly processes are good candidates for a cellular manufacturing system where continuous flow processing can be implemented in a rabbitchasing cell (Black, 1991). A rabbit-chasing cell is so named as the operators are essentially
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chasing each other in the cell. It allows one operator to work from the first process and all the way until the last process. After that, the operator will start the whole cycle again and work in
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a continuous loop.
71
Takt time 56
62
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63 sec
58
1 0
Deburring
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Stamping
Coating
Curing
Assembly
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Fig. 6. Process cycle time of each metal stamped part.
In order to introduce this rabbit-chasing cell, the curing process cycle time needs to be below the takt time (63 seconds). Hence, the curing process cycle time is proposed to be reduced to a time which is similar to the rest of the three processes. To do this, ‘kaizen’ is introduced. More details will be presented in the later section. 3.2.4
Where to use supermarket pull systems?
Besides the finished good supermarket, another two supermarkets are proposed. One of them is before the stamping process whereas the other is right after the stamping process.
ACCEPTED MANUSCRIPT To control the build-up of inventory before the stamping process, an internal withdrawal kanban system coupled with the supermarket can be implemented. This means that once the coils of stainless steel sheet are removed from the supermarket, a withdrawal kanban will be placed on the kanban post to signal to the production management department for ordering new supply. Currently, the raw material supplier makes a bi-weekly delivery which creates a
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sudden surge in inventory. To mitigate this issue, the option for the supplier to make daily delivery and in small amounts is proposed.
The other supermarket stores the parts after the stamping process. Whenever the rabbit-
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chasing cell withdraws bins of parts from the supermarket, production kanban will signal the stamping process to start production. With this pull system, there is no need for production management department to issue weekly production schedule to the stamping process and
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other processes in the cell. Since the pull from the shipping department has a kanban size of 50 parts, it is natural that a withdrawal kanban of 50 parts is implemented in the cell. This means that the production kanban which instructs the stamping process to start production can also have a size of 50 parts. Where is the pacemaker?
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3.2.5
The pacemaker process controls production at a process and sets the pace for the upstream processes. Since all the downstream processes of the pacemaker process need to be in a flow (Rother and Shook, 1999), the rabbit-chasing cell is naturally selected as the pacemaker. The
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stamping process cannot be the pacemaker as there is already a supermarket pull system between the stamping process and the cell. What is the incremental work to be released and taken away at the pacemaker?
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3.2.6
The incremental work to be disseminated is equivalent to the pitch. The calculation shows that pitch is 52.5 minutes for 50 parts (Fig. 7). This implies that the pacemaker should time itself to complete 50 parts in 52.5 minutes. This will be a useful gauge for the production management to know whether the process is smooth and on time.
ACCEPTED MANUSCRIPT Pitch = Bin size x takt time = 50 parts x 63 s = 3,150 s = 52.5 min
3.2.7
How to level production mix at the pacemaker?
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Fig. 7. Calculation of pitch for the pacemaker.
As MSP is the only one type of product in this case study, there is no need to level the production mix at the pacemaker. However, as MetalTech manufactures other products as
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well, there may be a need to ensure that the pacemaker produces in an even-level sequence. Hence, a load-levelling box or Heijunka box can be placed near the shipping process. Heijunka is a Japanese term which refers to levelled scheduling (Ohno, 1988). At the
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Heijunka box, the kanbans are placed in a mixed sequence. When the material handler pulls these kanbans out of the load-levelling box at the pitch increment minutes, this will trigger the withdrawal of parts from the supermarket after the pacemaker (the cell). As bins are pulled from the supermarket to the shipping process, the material handler will bring the production kanban to the cell. The cell therefore receives the instructions to produce the parts
3.2.8
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in the same time increment and sequence as the Heijunka box. What are the necessary process improvements?
To achieve the future state, there are a number of process improvements:
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1. Reduce the Changeover Time of the stamping process to improve OEE 2. Reduce the cycle time (71 seconds) of the curing process to be below takt time (63
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seconds)
3. Reduce large inventories by implementing a rabbit-chasing cell for continuous flow processing
These improvements are marked on the future state CVE-VSM as kaizen bursts. With the above information gathered by answering the eight questions, the future state CVE-VSM is drawn up as shown in Fig. 8.
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Fig. 8. Future state CVE-VSM of manufacturing the metal stamped part.
ACCEPTED MANUSCRIPT 3.3 Step 3 – kaizen events 3.3.1
Kaizen event 1
The goal of this kaizen is to reduce the stamping process Changeover Time. To do this, a widely adopted methodology to improve process Changeover Time is proposed (Abraham et
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al., 2012; Cakmakci, 2009; Chiarini, 2014; Dave and Sohani, 2012; Singh and Khanduja, 2010; Trovinger and Bohn, 2009; Ulutas, 2011). It is known as the Single-Minute Exchange of Die (SMED) methodology which originates from Shingo (1985). The word ‘SingleMinute’ does not mean that the changeover will take place in one minute. Instead, it refers to
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having a ‘single-digit’ minute Changeover Time. In other words, it is to achieve less than 10
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minutes in Changeover Time.
Source: (Moxham and Greatbanks, 2001)
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Fig. 9. Stages involved in Single-Minute Exchange of Die (SMED) methodology to reduce the Changeover Time of process.
In essence, SMED involves three major stages (Fig. 9). The first stage is to distinguish between internal and external activities for setup. Internal activities are activities that are carried out by stopping the machine. External activities are activities that can be done while the machine is still running. The second stage is to convert as much internal activities as possible to external activities for changeover. The key idea is to carry out most of the external activities simultaneously while the machine is still running. The third stage is to streamline all aspects of the set-up operation.
ACCEPTED MANUSCRIPT Table 9. Changeover Time could be reduced from 45 minutes to 15 minutes by converting internal activities to external activities.
Current
Planned
Time (mins)
Change the spool Unload current spool Return old spool Transport die from store Remove the current die from machine Set up the next die Test run Document the change
Internal Internal Internal Internal Internal Internal Internal Internal
External Internal External External Internal Internal Internal External Total
8 3 9 10 4 4 4 3 45
Time taken for internal activities only (mins) 3
4 4 4
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Activities
Table 9 identifies the current internal activities which can be converted to external activities in the future plan. If the external activities are running simultaneously while the machine is running, the Changeover Time only needs to consider the time taken for internal activities. Consequently, the Changeover Time can be reduced dramatically from 45 minutes to 15
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minutes, or a 67% reduction.
To further reduce the Changeover Time to 'single-digit', the next step is to focus on improving the efficiency of internal activities. To understand the possible issues which cause
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adopted.
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the inefficiency of internal activities, an 'Ishikawa' or a fishbone diagram (Ishikawa, 1982) is
Fig. 10. 'Ishikawa' diagram for root-cause analysis of inefficient internal activities.
From Fig. 10, five key issues were identified: 1. Lack of quick change clamp
ACCEPTED MANUSCRIPT 2. Improper clamping 3. Poor standard of operation 4. Lack of proper training 5. Untidy work area
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To address issues 1 and 2, the clamping system is proposed to be changed from a fixed clamp to toggle clamp. The benefits of the toggle clamp have already been demonstrated in a case study of implementing SMED for stamping production line (Abraham et al., 2012). Likewise, it is believed that the toggle clamp will be able to reduce the Changeover Time in this case.
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To address issues 3 and 4, proper documentation of Standard Operating Procedure (SOP) is recommended. Although SOPs are not uncommon, a common problem is that operators are not following them. Therefore, operators should be properly trained in the SOPs, and
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practising SOP should be an ingrained nature of the operators. To address issue 5, the implementation of the 5S technique is suggested. 5S comes from the Japanese words, Seiri, Seiton, Seiso, Seiketso, and Shitsuke. This is a proven technique which aims to improve the efficiency and effectiveness of a working environment through proper storage of items used, maintenance of the work area and items, and sustenance of an orderly work area (Chapman,
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2005; Chiarini, 2014; Pranckevicius et al., 2008; Slack et al., 2011; Web et al., 2006). The above practices are envisioned to be able to reduce the Changeover Time of the stamping process to be under 10 minutes. Kaizen event 2
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3.3.2
The goal of this kaizen is to reduce the curing process cycle time (71 seconds) to be below
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the takt time of 63 seconds. The target is 60 seconds since from the Lean perspective, it is better to have process cycle time lower than takt time. Furthermore, there may be issues in implementing the rabbit-chasing cell if the curing process cycle time is much longer than the other three processes cycle times.
The '5 whys' method (Wilson, 2009) is adopted to understand the root-cause of a long curing process cycle time. This method is a practice of asking why to a problem recursively until the underlying reason is discovered. Where simplicity is preferred, the '5 whys' method is a relatively simple to understand and straightforward to apply method (Ayad, 2010; Murugaiah et al., 2010; Tsao et al., 2000; Wilson, 2009). From Fig. 11, the underlying reason is due to uneven holes of the spraying nozzle of the coating equipment. Therefore, if the nozzle could
ACCEPTED MANUSCRIPT be replaced with a new one that has more even holes, it is possible to minimise over-coating. With less over-coating, curing time will be shortened since there is direct correlation between coating thickness and curing time.
Problem statement: The curing process cycle time is longer than takt
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time 1. Why does curing process take that long?
Reason: It has to ensure that sufficient time is allowed for proper curing of the coated layer
Reason: The coated layer is thick 3. Why is the coated layer thick?
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2. Why is sufficient time that long?
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Reason: The coating process has over-coated the layer 4. Why did the coating process over-coat the layer
Reason: There is uneven coating of the layer, with certain area of the layer being over-coated
5. Why is there uneven coating
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Reason: The spraying nozzle of the coating equipment has uneven holes due to wear and tear
Fig. 11. Adopting the '5 whys' method to understand the root-cause of a long curing process cycle time.
Kaizen event 3
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3.3.3
The goal of this kaizen is to reduce large inventories by implementing continuous flow processing, specifically a rabbit-chasing cell which combines deburring, coating, curing, and
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assembly processes (Fig. 12). This offers a few benefits: 1. Each operator can be crossed-trained so that the work is less monotonous. 2. Each operator can perform all the processes in the cell. Hence, the system can still function if anyone is absent. 3. The wait time between deburring, coating, curing, and assembly is eliminated. As a result, the work spaces that are currently used for inventory storage can be used for other purposes.
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Deburring
Coating
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Assembly
Curing
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Fig. 12. Implementing continuous flow processing that mimics the rabbit-chasing cell.
The proposed rabbit-chasing cell will require a total of four operators who will all start with
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different processes (Fig. 13). At the end of each shift, each operator will record the last process where he/she left off for resumption the next working day.
Operator
Deburring
Coating
Curing
Assembly
#2
Coating
Curing
Assembly
Deburring
#3
Curing
Assembly
Deburring
Coating
#4
Assembly
Deburring
Coating
Curing
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#1
Time
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Fig. 13. Proposed rabbit-chasing cell requires a total of four operators who will all start with different processes.
3.4 Step 4 – Action plan
The current state CVE-VSM gives a good overview of the existing operations and identifies some key issues. To overcome these issues, recommendations are proposed and captured in the future state CVE-VSM. However, the future state CVE-VSM is only a snapshot of the 'desired' status. To achieve the future state CVE-VSM, an Action Plan needs to be in place. The Action Plan (Table 10) details the proposed recommendations that address the issues, the
ACCEPTED MANUSCRIPT goals to be achieved, the timeline for implementation, the review date, and the people who
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are responsible for implementing the recommendations.
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Table 10. The Action Plan to document the proposed recommendations that address the issues, the goals to be achieved, the timeline for implementation, the review date, and the
Issue
Recommendations
Goal
Review Date
Responsibilities
1
Overproduction resulting in large inventories
Implement supermarket pull system and kanban system
To produce only what is needed and reduce large inventories
90 days
Every 30 days
• •
Production Manager Operators
2
Large delivery of raw material by supplier resulting in large inventories
Implement daily order and daily delivery of raw material in small batches
To order only what is needed and reduce large inventories
30 days
Every 15 days
• •
Production Manager Procurement
3
Long Changeover Time resulting in low Availability and OEE metrics
Implement SMED methodology; develop proper documentation of SOP; Provide training to operators; Implement 5S
To achieve less than 10 minutes of Changeover Time at the stamping process, and the goal of producing ‘every part every day’
90 days
Every 30 days
• •
Production Manager Operator at stamping process Tool designer
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Timeline
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S/N
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people who are responsible for implementing the recommendations.
•
Curing process cycle time is longer than takt time
Replace coating equipment current spraying nozzle with a new one that has more even holes
To achieve cycle time of 60 seconds
7 days
7 days
• •
Production Manager Operator at coating process
5
Non-continuous flow processing at deburring, coating, curing, and assembly process resulting in large inventories
Implement Rabbit-chasing cell
To achieve continuous flow processing and reduce large inventories
90 days
Every 30 days
• •
Production Manager Operators at deburring, coating, curing, and assembly processes
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4
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ACCEPTED MANUSCRIPT 4. Results and discussion Based on the above recommendations, the projected improvements are summarised in Table 11. By implementing the rabbit-chasing cell, the waiting time between each section is eliminated since the operator can only work at the next section after the same operator
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completes the work at the current section. Therefore, the production lead time from prior deburring to prior assembly can be reduced from 11 days to 2 days, or an 81.8% reduction! This will lead to an overall reduction in production lead time from 17 days to 6 days, or a
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64.7% reduction!
In terms of value added time, the reduction in curing process cycle time to below the takt
improvement.
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time will see the overall processing time reduced from 248 seconds to 237 seconds, or a 4.4%
Table 11. Summary of improvement based on the recommendations.
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Prior Stamping Stamping Prior Deburring Deburring Prior Coating Coating Prior Curing Curing Prior Assembly Assembly Prior Delivery Total
Production Lead Time (days) Before After 4 2 4.5
Value Added Time (s) Before After 1
1
2 56
3
62
2
236 71
1.5 58 2 17
2 6
248
237
Given the improvement in production lead time and value added time, the performance metrics for the future state will be improved tremendously. As shown in Table 12, there is a 170.8% improvement in the ratio of value added time and non-value added time (VAT/NVAT). This substantial improvement of VAT/NVAT is mainly due to the 64.7% reduction in non-value added time (NVAT). Consequently, the reduced amount of NVAT
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ACCEPTED MANUSCRIPT spent in using the facilities will lead to lesser amount of energy consumed for powering the facilities. The will lead to a 50% reduction in carbon footprint generated during non-value added time (CFPNVAT). From this result, it can be inferred that reducing NVAT has a significant and positive impact in improving both the Leanness and Greenness in production.
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The combination of 50% reduction in CFPNVAT and 6.4% reduction in CFPVAT will lead to a 29.9% reduction in total carbon footprint (CFPNVAT). Consequently, the CVE will be improved from 16.482 s/kg CO2e to 22.489 s/kg CO2e or a 36.3% improvement. This implies generated.
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that there is a 36.3% improvement in value adding activities per unit of carbon footprint
Table 12. The comparison of performance metrics between current state (before) and future state (after).
s s
Current state (Before) 248 856,800
%
0.029
0.078
170.8
kg CO2e
6.953
6.506
6.4
kg CO2e
8.094
4.047
50.0
kg CO2e s/kg CO2e
15.047 16.482
10.553 22.489
29.9 36.3
Unit
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Value added time (VAT) Non-value added time (NVAT) Ratio of value added time and non-value added time (VAT/NVAT) Carbon footprint generated during value added time (CFPVAT) Carbon footprint generated during non-value added time (CFPNVAT) Total carbon footprint (CFPTotal) Carbon-Value Efficiency (CVE)
Future (After)
Improvement (%)
237 302,400
4.4 64.7
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Metric
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Assuming the Changeover Time could be reduced to less than 10 minutes by the successful implementation of SMED in the stamping process, a sensitivity analysis is performed to project the possible improvement in OEE if Changeover Time is reduced. In Fig. 14, the Availability metric will increase from 86.19% to 94.76% if Changeover Time is reduced from 45 minutes to 9 minutes. Given the improvement in Availability metric, the OEE metric will improve from 78.93% to 86.78%.
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ACCEPTED MANUSCRIPT 100%
94.76% 95% 90%
86.19%
85% 80%
78.93% 75% 70% 45
39
33
27
21
Availability
OEE
15
9
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Changeover Time (min)
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86.78%
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Fig. 14. A sensitivity analysis projects the possible improvement in Overall Equipment Effectiveness if Changeover Time of the stamping process were to be reduced.
From the results, it is obvious that the implementation of Lean and Green practices can bring about improvement in production lead time, value added time, Availability and OEE. But besides these quantitative benefits, their implementation can bring about qualitative benefits
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as well. For instance, the implementation of 5S is likely to improve the working environment, leading to safer working conditions for the operators. By cross-training operators working in rabbit-chasing cell, their skill sets and employability will be boosted. Working as a team in
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implementing Lean strategies will foster team spirit and cohesiveness. In turn, this also builds greater trust between the management and employees, and gives them a sense of
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accomplishment in bringing value to their customers.
5. Conclusion and future work Despite strong correlation between Lean and Green, companies have found it challenging to integrate and implement both Lean and Green practices simultaneously especially when resources are limited. Although there are existing model, framework, and methodologies, some limitations and challenges still exist. This paper aims to overcome some of the limitations and challenges from the existing works. Specifically, one of the objectives is to
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ACCEPTED MANUSCRIPT propose a methodology that aims to integrate Lean and Green practices, and enables the implementation of the integrated Lean and Green practices in an easy and practical manner. To achieve this objective, the proposed methodology adopts and streamlines some of the approaches used in existing works. In this methodology, an easy-to-track metric called Carbon-Value Efficiency (CVE), which aims to integrate metrics derived from Lean and
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Green implementation, is introduced.
The other key objective is to demonstrate the applicability of the proposed methodology using a case study of metal stamped parts production. Through the use of CVE-VSM, the
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production lead time and value added time for the current state were captured. From there, several recommendations were made and a desired future state CVE-VSM was sketched out.
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To achieve the future state CVE-VSM, three kaizen events were proposed. Firstly, the Changeover Time of the stamping process should be reduced. This can be done through SMED. Secondly, the spraying nozzle should be changed to minimise over-coating issues. This will help to achieve a curing process cycle time that is below the takt time. Thirdly, a rabbit-chasing cell should be implemented for continuous flow processing which will help to
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reduce large inventories. These kaizen events and other Lean recommendations are to be put together in an Action Plan which would serve as a guide and commitment towards continuous improvement.
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Through these developments, several quantitative benefits could be realised. For instance, production lead time could be reduced by 64.7%, from 17 days to 6 days. In terms of value
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added time, the overall processing time could be reduced from 248 seconds to 237 seconds, or a 4.4% improvement. In addition, the carbon footprint could also be reduced by 29.9%. Given the improvement in production lead time, value added time, and carbon footprint reduction, the CVE could be improved by 36.3%. Besides improving CVE, the OEE metric could also be improved if Changeover Time of stamping process were to be reduced from 45 minutes to 9 minutes. This would lead to an increase in Availability metric from 86.19% to 94.76% and hence, an improvement in OEE metric from 78.93% to 86.78%.
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ACCEPTED MANUSCRIPT The results clearly demonstrate that companies can achieve quantitative benefits by integrating and implementing Lean and Green practices. But apart from that, these companies can also benefit from safer working conditions for the operators, improved skill sets and employability, improved team spirit and cohesiveness, greater trust between the management
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and employees, and a greater sense of accomplishment.
In summary, the two key objectives abovementioned have been achieved. Nevertheless, the proposed methodology still has room for improvement. For instance, even though some of the supporting tools and techniques have performed well in this selected case study, they may
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not be applicable in other case studies. Therefore, future work could extend the proposed methodology to other cases and explore other case specific supporting tools and techniques.
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Acknowledgments
We would like to acknowledge the company for providing data required for the study and all those who have contributed to this paper. We would also like to extend our gratitude to the reviewers for their valuable comments.
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References
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Highlights: Proposed a methodology to integrate and implement Lean and Green practices.
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Introduced an easy-to-track metric called Carbon-Value Efficiency.
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Demonstrated the methodology with a case study of producing metal stamped parts.
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Illustrated improvement in Carbon-Value Efficiency by 36.3%.
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Companies that integrate and implement Lean and Green practices can achieve beneficial
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results.