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Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia, March 8-10, 2016

Application of MFCA and ECRS in Waste Reduction: A Case Study of Electronic Parts Factory

Chompoonoot Kasemset Department of Industrial Engineering

Chiang Mai University Chiang Mai, Thailand

E-mail: [email protected]

Chawis Boonmee Division of Sustainable and Environmental Engineering

Muroran Institute of Technology Muroran, Hokkaido, Japan

E-mail: [email protected]

Penpatchara Khuntaporn Department of Industrial Engineering

Chiang Mai UniversityChiang Mai, Thailand

Abstract—The objective of this study is to apply Material Flow Cost Accounting (MFCA) and ECRS techniques to reduce material waste in the production of one electronic parts factory in Thailand. The seven steps of MFCA implementation were adopted to locate the source of negative product cost. From MFCA analysis, the negative product cost of material cost (MC) was the biggest amount comparing with other costs. Pareto chart was used to identify the major cause of the problem. Consequently, it was found that at the first process of trigger coil (target product) production line as frame cutting and injection had the highest negative cost of MC. Then, it was found that material waste in form of frame scrap generated at this process was from the inappropriate working method. Thus, the solution was proposed to design a new jig for the cutting operation. The results from MFCA analysis for the improvement showed that the total input cost was decreased from 22,444.46 to 22,300.92 THB and the negative product cost of MC was decreased from 2,557.10 to 2,437.21 THB. In addition, this solution can help in material reduction as 465.50 g. and gained more product as 2,000 pieces per production lot. Moreover, the total benefit for this product was approximately as 23,611.24 THB per month.

Keywords— Material Flow Cost Accounting (MFCA); ECRS; Electronic Parts Factory; Case Study

I. INTRODUCTION

Material Flow Cost Accounting (MFCA) is a technique that can help a factory to enhance both its environmental and financial performance, through the analysis of materials flows and energy usage. Thus, MFCA is applied for classifying costs of both positive and negative products. At the process with the highest negative product cost, the improvement solution is provided in order to reduce the negative product cost that can be implied to the reduction of waste for that process.

The case study factory is one electronic parts factory producing transformers and trigger coils for camera production. A lot of waste generated from the production line of this factory. In this study, one type of trigger coil is selected to be a target product due to its high production volume. To reduce waste generated from this production line will help in the company cost reduction, thus MFCA is considered to be adopted as identification tool for identifying the source of material waste. Then, the solution was proposed to reduce the waste depended on the cause of waste.

In this research work, there are four parts as introduction; preliminaries; methodology; case study and results; and conclusion and discussion to show how effectiveness of MFCA application to the case study.

II. PRELIMINARIES

A. Material Flow Cost Accounting (MFCA)Material Flow Cost Accounting (hereafter referred to as “MFCA”) was a method of environmental management accounting

that originated in Germany [1]. MFCA have been introduced to many industries such as electronic industries, food industries,

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fruit industries and others in Japan in 2011 by the ministry of economy, trade and industry of Japan to contribute improving both environment and economic impacts using advanced environmental management accounting approach. Thus, the ministry of economy, trade and industry of Japan proposed the inclusion of MFCA into the ISO to ISO/TC207 in 2008 [1] before MFCA was published as ISO 14051 in 2011. Through the concept of MFCA, the main objective is to identify the source of inefficiencies in material and energy use to find the solution to reduce waste [2].

Based on the concept of MFCA, any product cost can be classified as 4 categories as [2, 3]:

- Material Cost (MC) refers to a cost of each substance that enters and/or leaves a process,

- Energy Cost (EC) refers to a cost of electricity fuels, stream, heat, compressed air and other like media,

- System Cost (SC) refers to all cost of handing in-house material flows, such as cost of labor and maintenance, and

- Waste Cost (WC) refers to a cost of handing material losses/waste generated at each process.

Generally, the first step of MFCA is to select target product and process after that the target was analyzed by creating a material flow diagram as Fig. 1.

Process i

Newinputs

Inputs

Waste

Process i+1

Newinputs

Waste

Process i...

Newinputs

Waste

Finish Products

Material Flow Cost Accounting Boundary

Fig 1. Generic material flow model for target product/process within the MFCA boundary.

A material flow diagram presents clearly input, output and waste of each process (some research used the word “quality center” when there was more than one process grouped together). After that, cost allocation between the cost of positive product and the cost of negative product is carried out based on mass balancing method for each cost category. Classical method for mass balancing is to apply the direct weight of the product and waste to calculate the ratio of positive and negative product cost. In addition, other methods can be applied, such as indirect method and combination method, when the production line involving many material types with different measurement units [4].

To implement MFCA, there are seven steps as follows: (i) selecting the target product and process, (ii) collecting data and information, (iii) performing the MFCA calculation, (iv) identifying points for improvement, (v) introducing improvement methods, (vi) implementing improvement methods and (vii) evaluating improvement methods by performing the MFCA calculation again and comparing the results [5].

As MFCA can be used as identification tool for identifying the source of losses or waste along any production line, when the source is identified, different solutions can be proposed depended on the source of problems. For example, to reduced material waste in [6] proposed to improve the working procedure of workers in the small textile factory; [7] introduced the new working procedure for operators to reduce material waste in form of defect occurring when a machine is malfunction; [8] proposed to relocation the working area of one food processing company to reduced material waste from unnecessary transportation; [9] proposed new machine condition obtained from design of experiment (DOE) technique in wood processing to reduce wastes wood from the production line; [10] proposed new working method to reduce material waste in wood furniture factory.

B. ECRS Principle ECRS is one effective approach in process improvement. ECRS represents the four core concepts as [11, 12]:

• E: Eliminate waste found in manufacturing such as waiting time, unnecessary movement and work step.

• C: Combine unnecessary work steps to reduce the number of working step and total processing time.



• R: Rearrange any process step for reducing distance of moving or the number of movement.

• S: Simplify or propose easier method for working or introduce new equipment such as jigs, fixtures, support tools, or machine modification, to support operators.

ECRS is one common technique in motion study. Thus, when any process faces with inefficient working condition related to human works, ECRS was firstly considered and give the effective results after implementation. When ECRS was introduced to improve any process, the results were reduction in processing time and proposing efficient working steps that can reduce unnecessary movement and waiting time. The improvement from ECRS was affected to reduction in SC and EC when the processing time was reduced. In addition, MC and WC were reduced when the improvements were affected to reduce material loss from inappropriate working methods. The example research that applied ECRS and MFCA together can be found in [7, 8 and 10].

III. CAES STUDY AND RESULTS

A. MFCA Analysis – Current Situation

One of electronic industries in Thailand was selected to be the case study. Trigger coil was selected to be the target product of this study. The production line of trigger coil composes 6 processes: frame cutting and injection, winding, bonding and oven, waxing, bending, and packing. The material flow process chart of this production line can be shown as in Fig. 2.

From Fig. 2, all processes along the production line generated waste with no storing materials at each process. Then, MFCA analysis was carried out to identify costs along the production of trigger coil following equation (1) to (10) proposed in [4].

TCi = PCi-1 + MCi + SCi +ECi +WCi (1)

From equation (1), the accumulative total product cost (TC) at ith process is the sum of the positive product cost (PC) from the previous process, or at (i-1)th, and the new material, system, energy and waste management costs at current ith process. Output (positive) product cost at ith process or input cost (IC) at (i+1)th process is the sum of the positive material cost (PMC), positive system cost (PSC) and positive energy cost (PEC), as in equation (2).

PCi = ICi+1 = PMCi + PSCi +PECi (2)

Waste (negative) product cost (NC) at ith process is equal to the sum of the negative material cost (NMC), negative system cost (NSC), negative energy cost (NEC) and waste management cost, as in equation (3).

NCi = NMCi + NSCi +NECi +WCi (3)

The positive and negative product cost of the system cost can be allocated as shown in equations (4) to (7). When TSCi is the accumulative total system cost at ith process;

TSCi = SCi + PSCi-1 (4)

When Rpi is the proportion of positive product cost at ith process calculated by direct mass balancing from equation (5); Rpi = / (5)

PSCi = Rpi× TSCi (6)

NSCi = (1-Rpi) × TSCi (7)

The positive and negative product cost of the energy cost can be allocated in the same way, as shown in equations (8) to (10). When TECi is the accumulative total energy cost at ith process;

TECi = ECi + PECi-1 (8)

PECi = Rpi× TECi (9)

NECi = (1-Rpi) × TECi (10)

The results from MFCA analysis can be presented as Table I.



Fig 2. Material flow process chart of trigger coil

TABLE I. PERCENTAGE USED IN COST ALLOCATION FROM MASS BALANCE AND MC OF EACH PROCESS

Process Unit Positive Negative

Total Material Cost Material Cost

1. Frame cutting and Injection

Gram 3,638.75 1,366.25 5,005.00

Percentage* 72.70% 27.30% 100.00%

THB 1,047.45 319.55 1,367.00

2. Winding

Gram 4,446.25 85.00 4,531.25

Percentage 98.12% 1.88% 100.00%

THB 3,095.70 281.50 3,377.20

3. Bond and Oven

Gram 4,621.25 265.00 4,886.25

Percentage 94.58% 5.42% 100.00%

Baht 3,141.37 388.33 3,529.70

4. Wax

Gram 4,621.25 1,000.00 5,621.25

Percentage 82.21% 17.79% 100.00%

THB 3,141.37 1,350.00 4,491.37

5. Bending

Gram 10,046.25 190.00 10,236.25

Percentage 98.14% 1.86% 100.00%

Baht 10,363.15 173.17 10,536.32

6. Packing

Gram 10,003.05 43.19 10,046.24

Percentage 99.57% 0.43% 100.00%

THB 10,443.60 44.55 10,488.15 Note: *Rpi and 1-Rpi



Fig 3. MFCA analysis (Cost Unit: THB)

Total 2,204.63 4702.14 1347.75Newly input MC 1367 2329.75 434Newly input SC 412.5 1123.75 743.75Newly input EC 425.13 1248.64 170

previous Total 0.00 1656.43 6,021.14 process MC from previous process 0.00 1047.45 3,095.70

SC from previous process 0.00 299.90 1396.94EC from previous process 0.00 309.08 1528.50

Total 2,204.63 6,358.57 7,368.89 Input MC 1367 3,377.20 3,529.70 Input SC 412.5 1423.65 2140.69Input EC 425.13 1557.72 1698.50

27.30% 1.88% 5.42%

72.70% 98.12% 94.58%

Total 1656.43 6,021.14 6,772.35 Positive product MC 1047.45 3,095.70 3141.37Positive product SC 299.90 1396.94 2024.59Positive product EC 309.08 1528.50 1606.38

Total 548.20 337.43 596.55Negative product MC 319.55 281.5 388.33Negative product SC 112.60 26.71 116.10Negative product EC 116.05 29.22 92.12Waste treatment cost 65 0.35 2.19

meterials Selling prices 0 0 0

Total 1,530.25 10,163.45 2421.24Newly input MC 1350 7394.95 125Newly input SC 156.25 2737.5 1875Newly input EC 24.00 31 421.24

previous Total 6,772.35 6,274.60 16,155.33 process MC from previous process 3141.37 3141.37 10363.14819

SC from previous process 2024.59 1792.88 4446.29EC from previous process 1606.38 1340.34 1345.89

Total 8,302.60 16,438.05 18,576.57 Input MC 4,491.37 10,536.32 10,488.15 Input SC 2180.84 4530.38 6321.29Input EC 1630.38 1371.34 1767.13

17.79% 1.86% 0.43%

82.21% 98.14% 99.57%

Total 6,274.60 16,155.33 18,497.24 Positive product MC 3141.37 10363.15 10443.60Positive product SC 1792.88 4446.29 6294.11Positive product EC 1340.34 1345.89 1759.53

Total 2028.00 282.72 79.33Negative product MC 1350.00 173.17 44.55Negative product SC 387.96 84.09 27.18Negative product EC 290.04 25.45 7.60Waste treatment cost 0 5.36 2.1

meterials Selling prices 0 0 0Sales of byproducts and recycled

Percent quanlity of negative product

Percent quanlity of positive product

Positive product cost total

Negative product cost

5. Bending 6. Packing

Newly input total cost

Total cost handed over from

Process total of input cost

Negative product cost

Sales of byproducts and recycled

Cost item 4. Wax

Total cost handed over from

Process total of input cost

Percent quanlity of negative product

Percent quanlity of positive product

Positive product cost total

Cost item 1. Frame cutting and Injection 2. Winding 3. Bond and Oven

Newly input total cost



Then, the cost allocation for all costs and processes can be presented as Fig. 3 using percentage of positive and negative mass from Table I to allocate positive and negative costs of SC and EC as mentioned as equation (4) to (9). The results of cost allocation for this product can be concluded as Table II.

TABLE II. COST ALLOCATION OF ELECTRONIC PRODUCTION LINE BEFORE IMPROVEMENT (COST UNIT: THB)

MC SC EC WC Total

Input 13,000.70 7,048.75 2,320.01 75.00 22,444.46

57.92% 31.41% 10.34% 0.33% 100.00%

Positive 10,443.60 6,294.11 1,759.53 0 18,497.24

56.46% 34.03% 9.51% 0 100.00%

Negative 2,557.10 754.64 560.48 75.00 3,947.22

64.78% 19.12% 14.20% 1.90% 100.00%

Fig 4. Cost diagram of electronic parts factory

From Table II and Fig. 4, the results showed that the total cost of this production was 22,444.46 THB consisted of MC as 13,000.70 THB (57.92%), SC as 7,048.75 THB (31.41%), EC as 2,320.01 THB (10.34%) and WC as 75.00 THB (0.33%). The total cost can be allocated as the cost of positive and negative product as 18,497.24 THB (82.41%) and 3,947.22 THB (17.59%), respectively. Since, the largest portion of negative product cost was MC as 64.78%, the improvement was concentrated on reducing negative cost of MC. Based on mass balancing in cost allocation, when MC was reduced, the reduction of waste material quantity was consequently affected to reduction in EC and SC. The same result from reducing MC was directly affected in WC reduction as well.

B. Problem Finding To find to root cause of the negative cost of MC, Pareto chart was used to analyze material wastes from the production

line as Fig. 5. Using 80:20 rules, wastes from frame scrap and wax were approximately 80% from the total waste. In this study, waste from frame scrap was concentrated. From the observation, it can be identified that frame scrape was mainly occurred during cutting process because the inappropriate working method.

57.92% 56.46% 64.78%

31.41% 34.03% 19.12%

10.34% 9.51% 14.20%0.33% 0.00% 1.90%

0%10%20%30%40%50%60%70%80%90%

100%

Input Positive Negative

MC SC EC WC



Fig 5. Pareto diagram of material wastes

C. Improvement Planning and Proposing At 1st process (Frame cutting and Injection), the step of this process was at which the workers fixed the copper plate to the

jig before it was cut by the cutting machine. During this step a lot of waste was generated because to fix copper plate with the jig, tool holding allowance was needed for fixing the plate on the jig. By this working condition, after the plate was cut in pieces of work, the area of allowance was turned to be frame scrap. Fig. 6(a) presented the drawing of frame and jig with the size as 120x60 mm. The size of product is 16x20 mm. and the gap between each product row was 10 mm. Normally, one frame can be cut to produce 8 work pieces. The remaining frame after work pieces were cut was going to be the waste. The waste occurred as 1,341.25 g. per lot or 20,000 pieces.

The solution was proposed to design new jig at cutting process. Based on “S” or “Simplify” from ECRS concept, the new jig was proposed as Fig. 6(b). The new jig was designed to use for the same size of copper plate but reducing tool holding allowance from 13 mm. to 10 mm. and the gap between each product row from 10 mm. to 5 mm. This solution helped in reducing waste of copper plate scrap and increasing the number of product per one plate from 8 to 10 pieces. Consequently, as presented as Table III, material waste can be reduced to 465.50 g. as 34.71% reduction and total work pieces per lot increase to 22,000 pieces per lot.

(a)

1386.25

1000

160 110 80 60 50 43.19 35 250

200400600800

1000120014001600

Freme Wax Solder Pin Flux Glue Tape Coil Wire Resin

0.00

20.00

40.00

60.00

80.00

100.00

Mas

s (G

ram

e)

Cum

ulat

ive p

erce

nt



(b)

Fig 6. The cutting method of (a) Current and (b) Improvement

TABLE III. THE COMPARISON OF RESULTS BETWEEN BEFORE AND AFTER IMPROVEMENT

The number of copper waste (g.)

The number of product (pieces per lot)

Before improvement 1,341.25 20,000 After improvement 875.75 22,000

D. Evaluating Improvement Plan by MFCA Analysis The solution was evaluated by re-analyzing MFCA. The results from MFCA calculation was showed in Table IV. The

total cost after improvement was 22,300.92 THB that consisted of MC as 12,880.80 THB, SC as 7,048.75 THB, EC as 2,320.01 THB and WC as 51.36 THB. The total cost of positive product was 18,555.80 THB as 83.21% and the total cost of negative product was 3,745.13 THB as 16.79%. The comparison between Table 2 and Table 4 showed that the total input cost was decreased from 22,444.46 to 22,300.92 THB because the number of product per plate was increased. In addition, when the positive product cost of MC was equal as 10,443.60 THB, the negative product cost of MC was decreased from 2,557.10 to 2,437.21 THB. Fig. 7 presented cost comparison between before and after improvement situations. The comparison showed that the total product cost was reduced from 22,444.46 to 22,300.92 THB. Moreover, the percentage of total positive cost was increased from 82.41% to 83.21% while the percentage of total negative cost was reduced from 17.59% to 16.79%.

TABLE IV. COST ALLOCATION OF ELECTRONIC PRODUCTION LINE AFTER IMPROVEMENT (COST UNIT: THB PER 20,000 UNITS/LOT)

MC SC EC WC Total

Input 12,880.80 7,048.75 2,320.01 51.36 22,300.92

57.76% 31.61% 10.40% 0.23% 100.00%

Positive 10,443.60 6,322.95 1,789.25 0 18,555.80

56.28% 34.08% 9.64% 0.00% 100.00%

Negative 2,437.21 725.80 530.76 51.36 3,745.13

65.08% 19.38% 14.17% 1.37% 100.00%



Fig 7. Cost comparison before vs after.

IV. DISCUSSION AND CONCLUSION This study presented the application of MFCA and ECRS techniques in one electronic parts factory as a case study. The

target product/process was selected as a trigger coil product with 6 continuous processes. The results from MFCA showed that the main negative product cost was MC as 64.78% from the total negative product cost. Pareto diagram was presented that frame scrap at the first process was a major waste occurring during the frame cutting operation. Simplify from the ECRS principle was used to propose the solution to reduce material waste at this process. New jig design was proposed to reduce the area of the copper frame that should be cut away. From the proposed solution, waste from frame scrap can be reduced as 465.50 g. and gained more product as 2,000 pieces per production lot. Then, MFCA analysis was re-calculated and the results showed that the total input product cost was reduced from 22,444.46 to 22,300.92 THB and total negative product cost was reduced from 3,947.22 to 3,745.13 THB, while the total positive product cost was increased from 18,497.24 to 18,555.80 THB.

When the new jig design was proposed, the investment cost was approximately 1,500,000 THB. Since, this solution gave the total cost as 22,300.92 THB, the total cost can be reduced as 143.54 per lot when current cost was 22,444,46 THB per lot. The factory produces this product 6 lots per month, on average. The benefit from cost reduction and gaining more profit from additional 2,000 pieces were 23,661.24 THB per month. Thus, return of investment period is about 63 months or 5 years when considering only the benefit at the first process. In practical, the benefit from this improvement should be higher than this 23,661.24 THB when this solution is actual implemented the reduction in processing time from better working method can be affected on SC and EC reduction as well as the increasing in production capacity that can be used for producing other products. Thus, the factory should consider this amount of benefit carefully in order to make the decision on developing the new jig.

REFERENCES [1] Environmental Industries Office, Environmental Policy Division, Industrial Science and Technology Policy and Environment Bureau,

Ministry of Economy, Trade and Industry, Japan, “Guide for Material Flow Cost Accounting”, Retrieved from http://www.meti.go.jp, 2011

[2] A. Schmidt, U. Götze, and R. Sygulla, “Extending the scope of Material Flow Cost Accounting–methodical refinements and use case”, Journal of Cleaner Production, 2014

[3] DIN Deutsches Institut für Normung e.V.: DIN EN ISO 14051, “Environmental Management – Material Flow Cost Accounting – General Framework (ISO 14051:2011)”; German and English Version EN ISO 14051:2011, Berlin, 2011.

[4] C. Kasemset and C. Boonmee, “Different Cost Allocation Methods in Material Flow Cost Accounting: a Case Study of Waste Reduction in Thai Meatball Production”, CMUJ of Natural Science, in press.

[5] W. Chaiwan, C. Boonmee and C. Kasemset, “Application of Material Flow Cost Accounting Analysis Technique in Meat Ball Production”, International Congress on Logistics and SCM Systems 2015 Conference, Thailand, July 1-4 2015, pp. 183-193.

13,000 13,500 14,000 14,500 15,000 15,500 16,000 16,500 17,000 17,500 18,000 18,500 19,000 19,500 20,000 20,500 21,000 21,500 22,000 22,500 23,000

Before After

Cos

t (TH

B)

Total Cost (THB)

Positive Negative

82.41%

17.59%

83.21%

16.79%

22,444.46 22,300.92



[6] C. Kasemset, J. Chernsuporncha and W. Pala-ud, “Application of MFCA in waste reduction: case study on a small textile factory in Thailand”, Journal of Cleaner Production, pp. 1-10, 2014.

[7] C. Kasemset, S. Sasiopars, S. and S. Suwiphat, “The Application of MFCA Analysis in Process Improvement: A Case Study of Plastics Packaging Factory in Thailand”, Proceedings of the Institute of Industrial Engineers Asian Conference 2013, 353-361, 2013.

[8] W. Nakkiew, “Material Flow Cost Accounting in Dried Longan Manufacturer: A Case Study of Small-to-Medium Enterprise Company in Thailand”, EMAN-EU 2013 conference on Material Flow Cost Accounting Conference Proceedings, pp. 34-37, 2013.

[9] R. Chompu-inwai, B. Jaimjit and P. Premsuriyanunt, “Gainning competi-tive advantage in an SME using integration of Material Flow Cost Accounting and Design of Experiments: the case of a wood products manufacturing company in northern Thailand”, EMAN-EU 2013 conference on Material Flow Cost Accounting Conference Proceedings, pp. 141-144, 2013.

[10] A. Songkham and C. Kasemset, “Application of MFCA and Dynamic Programming in Operations Improvement: A Case Study”, Proceeding of ICIMSA 2015, Industrial Engineering, Management Science, and Applications 2015, Lecture Note in Electrical Engineering, Springer-Verlag Berlin Heidelberg, pp. 35-44, 2015.

[11] C. Kasemset, P. Pinmanee and P. Umarin, “Application of ECRS and Simulation Techniques in Bottleneck Identification and Improvement: A Paper Package Factory”, Proceedings of the Asia Pacific Industrial Engineering & Management Systems Conference 2014, October 2014.

[12] K. Wajanawichakon1 and C. Srimitee, “ECRS’s Principles for a Drinking Water Production Plant”, International Organization of Scientific Research (IOSR), Vol. 2(5), pp. 956-960, 2012.

BIOGRAPHY Chompoonoot Kasemset is an assistant professor in the department of industrial engineering, faculty of engineering, Chiang Mai University, Thailand. She received a D.Eng. in Industrial Engineering and Management, School of Engineering and Technology at Asian Institute of Technology in 2009. Her research interests include operations management, applied operations research, simulation application in production management and Material Flow Cost Accounting (MFCA). Her special field is Theory of Constraints (TOC). Chawis Boonmee is a doctoral student in division of sustainable and environmental engineering, Muroran Institute of Technology, Japan. He received the M.Eng. degree in industrial engineering from Chiang Mai University in 2015 and the B.Eng. degree (2nd class honors) in field of industrial engineering from Chiang Mai University in 2012. He interested in the field of industrial engineering including optimization, operation & supply chain management, simulation application in production management, decision making and Material Flow Cost Accounting (MFCA). Penpatchara Khuntaporn is a graduated student in field of industrial mangement, department of industrial engineering, faculty of engineering, Chaing Mai University.


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