Operational Performance Metrics in Manufacturing Process: Based on SCOR Model and RFID Technology

Operational Performance Metrics in Manufacturing Process: Based on SCOR Model and RFID Technology Gyusun Hwang, Sumin Han, Sungbum Jun, and Jinwoo Park Abstract Performance measurement is the fundamental activity to evaluate the competitiveness of a company. By suggesting the method of performance measurement, we can expect that the result can affect several management components consisting of following three levels: Strategic level, Tactical level, and Operational level. However, the metrics belonging to different levels are not integrated, therefore a huge gap among the different levels exist. So this paper covers the metric-gap among these levels, and finally focuses on the performance of operational level. In order to achieve this purpose, we review the SCOR model and define the problems of the metrics in SCOR model. The aim of this paper is to develop a process for tracking the metrics of the operational level with the ERP systems. As the result of study, we expect that the performance of several key metrics can be automatically measured in real time. To do this, we design the procedure of measuring performance and extracting the possible metrics of RFID on the operational level when RFID is implemented to a SCOR model based ERP system. remains an important subject in recent studies. SCOR model, which is the reference model of this paper, covers all of the supply chain management (SCM). Due to its wide range of concerned, the scope of this paper is limited in the manufacturing aspects. In general, there are hierarchy levels in company s management components. And they are strategic, tactical, and operational levels which are distinguished by their duties, positions, job tenure, etc. Top management in strategic level needs financial measures for management level decisions. But lower management situated in tactical and operational level and workers need operational measures for daily business [1]. Index Terms Performance measurement, performance metrics, SCOR model, RFID (radio frequency identification) technology, ERP system. I. INTRODUCTION To compete in the global markets, organizations strive to make the outstand performance. And evaluating an appropriate performance is a key role in company s success. For this reason, performance measurement has gained a tremendous amount of the attention, because it has a significant influences on performance themselves. The lack of proper performance measure will result in failure to meet customer needs. And this result causes the company s low competitiveness and provokes the low profit business, if bad performance measurement is lasting. It is generally believed that a well-extracted metrics can increase the chances for success by inspecting the entire process of the company environment. And result of the performance measurement delivers company s competitive advantages through correcting the company s defects. In manufacturing company, operational performance has a major impact on product cost, product reliability, cycle time, etc. So the measurement of manufacturing performance Manuscript received December 31, 2013; revised February 10, 2014. This work was supported in the ASRI (Automation and Systems Research Institute) in Seoul National University in the form of resources and administrative support. The authors are with the Dept. of Industrial Engineering at Seoul National University, Seoul, Republic of Korea (e-mail: skyair21@mailab.snu.ac.kr, hans8501@mailab.snu.ac.kr, junsb87@mailab.snu.ac.kr, autofact@snu.ac.kr). Strategic level Tactical level Fig. 1. Characteristics measurement of management level. Operational level TABLE I: METRICS IN MANAGEMENT LEVEL Metrics Lead time, Quality level, Cost saving, Supplier pricing, Order cycle time, Cash flow, Total cash flow time, Capacity, Rate of return on investment, Level of customer perceived value of product, Net profit vs productivity ratio, Range of product and services, Variations against budget Accuracy of forecasting techniques, Effectiveness of master production schedule, Flexibility, Customer service satisfaction, Customer query time, Order entry method, Flexibility Defect free rate, Capacity utilization, Lead time, Range of product and services, Effectiveness of scheduling techniques, Incoming stock level, Work in progress, Finished goods in transit There is a lack of a clear distinction between metrics at strategic, tactical, and operational levels. These limitations should be complemented by balanced approach. And metrics and measurement should be classified at strategic, tactical, and operational levels, and be non-financial measures, as well. Gunasekaran et al., present the metrics regarding the DOI: 10.7763/IJIMT.2014.V5.485 50

management levels [2]. And Table I presents the metrics in each management level regarding the manufacturing process. II. PERFORMANCE MEASUREMENT AND METRICS A. Performance Measurement Performance measurement is indispensable for managing the state of the system and taking the appropriate actions for maintaining company s competitiveness. And many companies conduct performance measurement for measuring, evaluating, and monitoring their operations of the entire activities [3]. Fig. 2. Functions of performance management. There are some important criteria for effective performance measurement. 1) The measures should link between strategy, execution, and value creation. And the measures should indicate the comprehensive performance of activities. Performance measurement takes into account the overall company s activities. In order to achieve this, measures should align the activities from business to operations. 2) The measures should involve relevant non-financial and intangible dimensions of performances. In general, especially in Top management level, financial measures are frequently used to gauge the performance or the firm. But on the point of the low management level s views, there are many aspects concerned with intangible performances such as effectiveness of the scheduling, human resource related measures, etc. And those non-financial measures also important factors required to manage the company s activities. 3) The measures should capture the reality adequately. As the circumstance of the company s environment is dynamic status, measures could be obsolete. And this obsolete prevent the measuring the performance effectively. So measures should represent the actual circumstance of the company s environment. 4) The measures should be observable and measurable which have quantitative terms. And this criterion ensures that measures can be applied to the analytic method. In short, measure must be a simple, intuitive, and easy to evaluate the performance. And measure has to be pervasive which represent to the circumstance of the system. B. Metrics Characteristics Related with the Manufacturing Performance The metrics are very important source of the performance measurement, because most of the performance measure is evaluated by the metrics. There should be inefficiency and disruption in manufacturing interactions, if metrics are falsely collected or misaligned. Therefore, appropriate metrics should be extracted. The appropriate performance metrics can be used to evaluate the probability of success in achieving the target, to provide advice or corrective suggestions to the organization, to evaluate the internal input and output [4]. Fig. 3. Flow of the performance analysis. The metrics used in operational level are to reflect the current status of manufacturing situation [5]. In the shop level, there are many machines and work in process (WIP) parts exists. Metrics are critical elements in representing the dynamic circumstance of the shop environment. So metrics also should be changed rapidly in order to prevent metrics becoming the obsolete. And operational metrics should monitor and control the operational efficiency. Finally, operational metrics are used to gauge and measure how a manufacturing business is performing, which is measure of how effectively the operations and business is achieving its defined goals. The metrics are related to the specific manufacturing goals. And metrics reveal a real insight of performance measurement, the appropriate performance measures that best suit the operational level context are required. Finally, the metrics are to drive the effectiveness of manufacturing decisions. Extracting the effective metrics follows this procedure: First, Identify the defining elements and different metrics. Second, Position the metrics within the operations management research environment. Third, identify the special research challenges associated with metrics. Finally, introduce the articles that comprise the special issues [6]. III. SCOR MODEL A. Introduction of the SCOR Model The supply chain operations reference (SCOR) model is a 51

business process reference model. It covers all elements of demand satisfaction process that begins with the initial signal of demand and ends with the final signal that demand has been satisfied. The SCOR model integrates the concepts of Business Process Reengineering, benchmarking, process measurement. Adopting the SCOR model is helpful for mangers to standardize the description of supply chain, which is useful to form a unified understanding. The SCOR model advocates hundreds of performance metrics used in conjunction with five performance attributes: Reliability, responsiveness, flexibility, cost, and asset metrics [7]. The structure of the SCOR model includes four levels that represent the company s activity covering front-end and back-end. SCOR model presents the five primary management processes: Plan, Source, Make, Deliver, and Return. Fig. 4 presents the structure of the SCOR model primary process. Fig. 4. The end to end processes of the SCOR model. TABLE II: SCOR MODEL ASPECTS (MANUFACTURING) [8] Process Make to Stock (M1) Make to Order (M2) Engineer to Order (M3) Aspects Cash to Cash Cycle time Cost of Goods Sold Cost to Make Downside Make Adaptability Make Cycle Time Order Fulfillment Cycle Time Return on Supply Chain Fixed Assets Return on Working Capital Upside Make Adaptability Cash to Cash Cycle time Cost of Goods Sold Cost to Make Downside Make Adaptability Make Cycle Time Order Fulfillment Cycle Time Perfect Order Fulfillment Return on Supply Chain Fixed Assets Return on Working Capital Upside Make Adaptability Cash to Cash Cycle time Cost of Goods Sold Cost to Make Downside Make Adaptability Make Cycle Time Order Fulfillment Cycle Time Return on Supply Chain Return on Working Capital Upside Make Adaptability This study limited its scope to the manufacturing aspects, we consider the Make primary management process. And J. What presents manufacturing related aspects in SCOR model [8]. This study enumerate the metrics in terms of 3 processes: Make to Stock, Make to Order, and Engineer to Order. And each aspect includes many financial and nonfinancial metrics. B. Problem Definition There are too many metrics in the SCOR model. And this problem makes some problems. 1) Large number of metrics makes it difficult to identify the actual circumstance. 2) SCOR model does not present the connecting method between performance measurement and the information system. 3) Those metrics have inter-correlated relationship, because metrics are organized in the hierarchical structure. 4) Those metrics cannot be measured by data-set based and it brings about the additional work if they take a performance measurement To solve those problems, this study reorganizes the operational metrics taking about 64 metrics. And we also present the method of the automatic performance measurement method by adopting the RFID technology. Inserting the performance measurement method into the ERP system may reduce the additional work conducted for performance measurement. IV. MANUFACTURING PROCESS AND ENTERPRISE RESOURCE PLANNING (ERP) IN PERFORMANCE MEASUREMENT In an attempt to provide a better understanding of how the manufacturing function can be used to support corporate objective, this figure shows the overall process of company activities. Fig. 5. Flow chart of the overall process. From the sales and marketing functions to the customer order status, many processes are participated to complete the activities. And those overall processes are area of the SCOR model. As we focus on the manufacturing process, we only consider Inventory available, Credit Check, Production Schedule, Purchasing, Back Order, Inventory File, Production [9]. And we also deal with the direct linking area such as Customer Oder and Process Order, because those activities strongly influence on the manufacturing process. Since the late 1980 s, many companies have been 52

implemented their Enterprise Resource Planning (ERP) system to improve their business performance. ERP system is applied to manage their activities in the core business process by using common database. And the ERP systems monitor business resources such as cash, material, and production capacity. Therefore, performance measurement can be executed in the ERP system, because it covers overall company s activities and has a common database. In order to achieve measurement, key areas of a manufacturing processes and ERP systems should be identified. Fig. 6 shows the process of the manufacturing modules in ERP system. Fig. 6 includes the traditional manufacturing planning and control (MPC) system [10] and several components with the view point of performance measurements. Fig. 6. Process of the manufacturing module in ERP. As shown in the Fig. 6, sales and operation plan links the design of a firm s MPC system with its business strategy. And this plan acts as the input data of the Master Production Scheduling (MPS). MPC system includes Material Requirement Planning (MRP) and other planning processes. Finally, all of the processes are concentrated on the Measurement of Performance. If bad performance is detected during the business process, appropriate managerial decision may not be available until the decision may have to be made based on activities outside of the system. This result will bring about bad responsiveness in the dynamic manufacturing environment. By this reason, appropriate performance measurement is important to accomplish the real time measurement in ERP system. And detailed procedure of the performance measurement for an ERP system is suggested in next section. V. RFID (RADIO FREQUENCY IDENTIFICATION) TECHNOLOGY RFID technology is a conceptually simple technique, because data is stored in RFID tags which are attached to objects or located in smart cards. The data tags can be accessed by using radio signals and presented on a display by using a portable RFID reader. Also the data in RFID tags can be transmitted automatically to an Information Technology system for further processing [11]. By application of the RFID technology, the information of manufacturing process can be transferred to the Enterprise Relationship Planning (ERP) in real time. Furthermore the information can be treated as the performance evaluation automatically. Many of the activities in those systems are reported manually and prone to data entry mistakes forcing the system to be less reliable than it could be [12]. By taking the RFID technology, we can take much more reliability and increase the speed at which the data is transferred to the ERP system with a higher accuracy. From the supply chain, the RFID technology has been gradually applied in the production process. For this reason the appropriate design and implementation of RFID-based system attracts many researcher s attention [13]. However, there are very few real case applications that can be examined, such as RFID-based production process monitoring and analysis [14]. In the score model driven system, RFID technology is helpful for tracking and tracing of all entities automatically, including materials, WIP, the location of fixed and mobile resources, etc [13]. The tracking of manufacturing process realizes the resource management and performance measurement much more efficiently and automatically. In order to achieve this, we introduce the RFID-based performance evaluation metrics which integrates the operational process and ERP system. RFID devices are deployed to the shop process, conveyors, batch, pallets, etc., and those are converted as the meta-data. And meta-data are able to be translated as the performance metrics which act as the measurement of the operational process. We analyzed the SCOR model 9.0 version and extracted metrics which are able to link between operational level and RFID criteria. Table III presents the SCOR model metrics related with RFID [15]. Attributes Reliability TABLE III: SCOR MODEL METRICS RELATED WITH RFID Responsiveness Agility Cost Asset management Operational metrics % Item Location Accuracy % of products meeting specified Environmental performance % of products with proper environmental labeling % Orders/ Lines Processed Complete % Product Transferred without Transaction Errors Schedule Achievement Balance Production Resources with Production Requirements Cycle time Manage In-Process Products Cycle Time Schedule Production Activities Cycle Time Stage Finished Product Cycle Time Time To reach and sustain current Transfer Product Cycle Time Verify Product Cycle Time Finalize Production Engineering Cycle Time Issue Material Cycle Time Produce and Test Cycle Time Schedule Production Activities Cycle Time Stage Finished Product Cycle Time manufacturing order cycle Time Additional make volume Current source volume % of pallets that are usable Capacity utilization (Finished Goods ) (Raw Material ) ( WIP ) Percentage Excess Inventory 53

Most of the metrics take charge of activities such as inventory management, cycle time management, pallet management, production process control, sorting order, and production flexibility management. Meta data created by RFID can be interchangeable with SCOR model. And those data can be translated into the performance measurement in the ERP system. Considering those metrics, we designed the procedure of the performance measurement in ERP system. The SCOR model, RFID technology, manufacturing system, and ERP system are also considered. This figure presents the procedure of the performance measurement in ERP system. has been developed which attempts to explain the mechanism of the performance measurement in ERP system. This procedure links different measures of operating performance: RFID, SCOR, Production, ERP system. Performance measurement will be executed automatically with effectively and high accuracy, if this procedure works well. Further research is required for some reasons. First, extracting the operational metrics regarding SCOR model and RFID technology should be completed by the design of the hierarchical structure. Then, detailed implementation method to adopt in ERP system is to be developed. Through the further research, we are able to draw the new system architecture for automatic performance measurement. ACKNOWLEDGMENT We would like to acknowledge the support by the ASRI (Automation and Systems Research Institute) in Seoul National University in the form of resources and administrative support. Fig. 7. Procedure of the performance measurement in ERP system. From the SCOR model, there are five primary management processes: Plan, Source, Make, Deliver, and Return. And Make process includes operational metrics which represent the manufacturing process environment. Management level which has strategic, tactical, operational level considers Planning, Execution, Enabling activities. In the scope of the SCOR model, there are many data considering the circumstance of the manufacturing management. And the adoption of RFID technology makes meta-data regarding the shop circumstance such as cycle time, pallet speed, etc. Production data, which is received from the low level manufacturing system such as Manufacturing Execution System, Batch system, etc., acts as the other source of the performance measurement. Finally ERP system database included information of management status also acts as the performance measurement. Those metrics are the source of the performance measurement in ERP system. And the result of the measurement will transmit to the management level. This feedback loop works as the continuous improvement motivation within the company s activities. VI. CONCLUSION While the performance measurement studies present the metrics without considering of the gap among strategic, tactical, operational level. This study arranged the refined operational level metrics and connects the RFID related measurement. We analyze the process of the manufacturing module in ERP system. And the result of the analysis is that a procedure REFERENCES [1] I. Sillanpää and P. Kess, The literature review of supply chain performance measurement in the manufacturing industry, Management and Production Engineering Review, vol. 3, issue 2, pp 79-88, 2012. [2] A. Gunasekarana, C. Patel, Ronald, and E. McGaugheyc, A framework for supply chain performance measurement, International Journal of Production Economics, vol. 87, issue 3, pp. 333 347, Feb. 2004. [3] K. K. B. Hon, Performance and Evaluation of Manufacturing Systems, CIRP Annals - Manufacturing Technology, vol. 54, issue 2, pp. 139 154, 2005. [4] Y. D. Hwang, Y. C. Lin, and J. L. 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Gyusun Hwang was born in Kwangju, Republic of Korea on 29 th October 1986. He received his bachelor s degree in management information system from HanYang University, Seoul on 2011. At 2011, He entered the graduated school of Seoul National University. And He received master s degree in industrial engineering from Seoul National University in 2013. Now, He is in Ph. D. course of Seoul National University. His research interest is in manufacturing system, Management Information System, and performance measurement. Sumin Han was born in Seoul, Republic of Korea on January, 1 st, 1985. He got bachelor s degree in industrial engineering from Seoul National University, Seoul on 2010. At 2010, He entered the graduated school of Seoul National University. His research interest is in manufacturing system, software development process, and emergency logistics. Now, He is in Ph. d. course of Seoul National University. He participates in the various research projects related to manufacturing system and emergency response systems. Sungbum Jun was born on 21 st July 1987 in Seoul, Korea. He received his bachelor's degree in industrial engineering from Seoul National University. Since 2012, he has studied for his master degree in industrial engineering at Seoul National University. His current research interests are in manufacturing systems engineering, simulation and scheduling. Jinwoo Park was born in Seoul, Korea on December, 18 th, 1952. In 1985, he received a Ph.D. degree in industrial engineering at University of California, Berkeley and now he is a professor of Industrial Engineering at Seoul National University. His current research interests are in manufacturing systems engineering, simulation, scheduling, Enterprise Resource Planning/Supply Chain Management and Flexible Manufacturing System/CIM. He is a member of Institute of Industrial Engineers (IIE), Society of Manufacturing Engineers (SME), Association of Computing Machinery (ACM), Institute of Electrical & Electronic Engineers (IEEE), American Production & Inventory Control Society (APICS). 55