E-MANUFACTURING: THE KEYSTONE OF A PLANT-WIDE REAL TIME INFORMATION SYSTEM

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1 266 Journal of the Chinese Institute of Industrial Engineers, Vol. 20 No. 3, pp (2003) E-MANUFACTURING: THE KEYSTONE OF A PLANT-WIDE REAL TIME INFORMATION SYSTEM Robin G. Qiu * Dept. of Information Sciences Pennsylvania State University Great Valley Malvern, PA 19355, USA ABSTRACT The Internet and advanced network computing technologies have made real-time and integrated business logic transactions a reality. As a result, the adoptions of e-business in enterprises are accelerating across all the business sectors around the world. For a manufacturer a plant-wide real-time information system is fundamental to its e-business execution, where an e-manufacturing System (EMS) on the plant floor plays a key role. This paper presents an approach to the implementation of an EMS. First, by incorporating the concept of Virtual Production Lines (VPL) into an EMS, the computations of the EMS can be distributed across networks, resulting in a satisfactory performance. Secondly, a generic equipment operation model and generic operations are introduced from an EMS perspective, which not only make system integration easier but also guarantee the real-time entries of system data for all the activities occurred on the plant floor. EMS real-time responses enhance the office planning system and thus would promote the e-business deployment for a manufacturer. Keywords: e-manufacturing system, manufacturing execution system, virtual production line 1. INTRODUCTION The advances in Information Technology have continuously made enterprises capable of achieving high productivity with better quality at lower cost. Nowadays enterprise operations are heavily dependent upon effective deployment of information systems, although the scope and detailed functionality in an enterprise information system may vary widely with an enterprise process mode (continuous, batch, discrete, assembly, or mixed mode) and business execution style (make-to-stock or make-to-order). By abstracting both office and plant floor information systems running in industry a well recognized enterprise-wide information context model has been generalized, which is illustrated in Fig. 1 (a) [5]. The functionality in this model can be summarized as follows [5]: Enterprise Resources Planning (ERP) (formerly termed as Manufacturing Resource Planning (MRP II), Material Resource Planning (MRP), or Master Schedule System) provides enterpriselevel management functions, such as financials, order management, production and materials planning, market analysis, human resource, e- marketplace, business-to-business, enterprise virtual factory/manufacturing management, and so forth. Supply Chain Management (SCM) includes functions such as supply forecasting, logistics and distribution, procurement management, and supplier and customer collaborations. Sales and Service Management (SSM) comprises software for sales force automation, product customization, service quoting, and product returns. Customer Relationship Management (CRM) takes responsibility on market broadening, customer satisfactions and retention. Computer-Aided Engineering (CAE) -- covers computer-aided design and manufacturing (CAD/CAM), process modeling, engineering test, cost analysis, and product data management (PDM). Plant Floor Controls are usually hybrid hardware/software systems such as programmable logic controllers, distributed numerical controls, supervisory control and data acquisition systems, robotics systems, material transport systems, and other computerized process control designed to control the operations and activities through which products * Corresponding author: robinqiu@psu.edu

2 Robin G. Qiu: E-Manufacturing: the Keystone of a Plant-Wide Real Time Information System 267 CRM SSM EMS Office Information Systems MCS SCM ERP CC MTS EMS CAE EGC EGC EGC Manufacturing Cell Cell Controls (a) EMS: e-manufacturing System MCS: Material Control System MTS: Material Transport System EGC: Equipment Group Controller CC: Cell Controller Figure 1. (a) Enterprise information model (b) Plant floor information model (b) are being manufactured on the plant floor. E-Manufacturing Systems (EMS) consist of plant-wide floor information systems providing real-time manufacturing information to effectively execute operations to meet business goals. As shown in Fig. 1 (a) EMS fills the gap between office planning and plant floor manufacturing and makes it possible to have a realtime plant-wide view of critical processes and production status that are necessary for timely office decision-making and optimal factory manufacturing executions. More details regarding the plant floor information model are shown in Fig. 1 (b). The modules used on the plant floor are briefly defined below: Cell Controller (CC) Major functions include the execution of assigned tasks within the cell and cell activity monitoring. An EMS client can reside in a CC. In other words, a CC can be an instance of the EMS Equipment Group Controller (EGC) Its role is to govern a group of equipment. An EGC oversees the status of all the equipment in the group. In addition, process plans or routing logics can be archived and retrieved from an EGC. Material Transport System (MTS) Local material delivery management is the key function of an MTS. By effectively and efficiently executing the material delivery tasks, MTS guarantees that materials be delivered to a right machine at right time. Material Control System (MCS) It controls the material movement between manufacturing cells. More importantly it provides the overall view of material statuses and optimal material delivery paths on the plant floor from the system perspective. Apparently only EMS is capable of giving a plant-wide view of the status of processes, materials, consumables, human resources, machines, and tooling on the plant floor. On one hand, by recording results of activities in the plant an EMS always feeds data to the office information systems. On the other hand, EMS takes in data from these office information systems, ensuring that their information is acted on optimally and intelligently in the plant [1]. Integration between an EMS and the other major office information systems thus becomes a key to gaining full benefits not only from the EMS but also from these office information systems. Although many manufacturers have been building computer-integrated manufacturing systems and management information systems in one way or another to stay in cutting-edge technology and keep competitive since the 1980s, due to the lack of sufficient investments from governments and industries, most plant manufacturing floors are still not well integrated with office information systems [7, 11]. By focusing on both real-time response and system integration issues, this article discusses an approach for different size enterprises in different industries to be able to put EMSs into use, thereupon plant-wide real-time information systems can be successfully realized. 2. REAL-TIME RESPONSES As discussed above the concept and capability of having data available in real time is fundamental to

3 268 Journal of the Chinese Institute of Industrial Engineers, Vol. 20 No. 3 (2003) a plant-wide information system. Fig. 2 shows how office information systems, EMS, and plant floor operations could be timely integrated from the data flow perspective. EMS not only provides office information systems with the real-time supervising capability to monitor and control the floor activities, but also provides fast and optimal reactions to plantfloor activities and changes by being integrated with finite capacity scheduling and intelligent executing applications [4]. That is to say, in addition to supervision and controls EMS must continually analyze these activities and changes in real-time in order to be responsive to scheduled and nonscheduled events as they are occurring on the plant floor. In essence, the production knowledge both of what is actually happening, and of what should happen is completely captured in the EMS. It is here that the overall effectiveness of a plant is both guided and measured [1]. Because of the high cost of deployment of automated manufacturing systems [1, 3, 6, 7], machines are not yet wholly integrated on most plant floors. Even though many machines are automationready, the deployed manufacturing execution systems in the industry gathers most data from the plant floor through manual inputs at user s discretion [2, 3, 11]. When controls are made in seconds or fractions of seconds in floor process execution systems, the manufacturing execution system takes minutes, hours, or even days to respond to them. Compared to the chaos of old plant floors where no electronic plant floor information was available and ERP or other office systems were implemented as open loop systems with response times in days, or weeks, the currently existing manufacturing execution system solutions are relatively real time. The scalability of an existing manufacturing execution system is also very much limited in terms of the capability to keep its real-time responses at satisfactory resolutions when the governed manufacturing system grows. The following evidences in enhanced or up-scaled manufacturing systems show manufacturing execution system realtime responses in terms of time resolutions are getting worse: The amount of information collected from control systems increases tremendously with the degree of increased automation on the plant floor. That is to say, manufacturing execution systems are required for processing more information. Manufacturing systems grow due to the requirement of more complex processes to meet the needs of increasing product functionality. In other words, manufacturing execution systems are required for being either physically or logically connected to more equipment and accordingly acquiring tremendously more data. In addition, to continuously improve the productivity of enterprise manufacturing systems, a Customer Orders Work Orders, Work Instructions, & Engineering Instructions Control Parameters, Operator Instructions, & Consumable Information Office- Information System Time Factor > 1000x e-manufacturing System Time Factor > 100x Automated Control System or Manual Operations Time Factor = 1x Customer/ Supplier Needs Order Status Product Data Quality Data Production History Sales History Customer Data Supplier Data Engineering Data Updating Office- Planning System Production Status Equipment/Device/People Status Process Data Checking Resources Releasing Work Orders Tracking WIP Adjusting Process Plans Display Operator Instructions Intelligent Maintenance Controlling Equipment Activating Devices Manual Operations Data Entry Figure 2. Enterprise view of EMS real-time response [4]

4 Robin G. Qiu: E-Manufacturing: the Keystone of a Plant-Wide Real Time Information System 269 deployed manufacturing execution system has to get all the manufacturing processes and product data from all the plants geographically dispersed across the world in time. These data should also be analyzed in real time in order to make enterprise-wide optimal decisions. Here are three examples: Manufacturing execution systems will be used to validate manufacturing processes. As soon as materials move into equipment, a manufacturing execution system validates the equipment setup and production schedule, and then gives the goahead command to initiate the operation. A realtime response becomes critical since no equipment should wait minutes for any operation initiation. Statistical process control (SPC) will be used to control rather than monitor equipment. Currently, SPC is implemented as an open-loop function in a manufacturing execution system. It monitors the process status and indicates the trend of product quality. Once the process does not satisfy the requirement, SPC gives off an alarm. But when SPC is actually used to control equipment, it has to be capable of sending prompt feedback back to the equipment. The response time back to the equipment cannot be in a minute order of magnitude. Parts could be made in different plants. Thus production and resource data need to be shared among various plants to react more quickly to customer orders using the optimal executions in terms of enterprise-wide decision-making. With the fast development of the Internet and network computing technologies a manufacturing execution system is evolutionarily transformed into e- Manufacturing. The key of e-manufacturing is that all the plant floor information will be electronic and information flow on the plant floor will be real-time with satisfied time resolutions. As the keystone for the deployment of a plant-wide real-time information system, typical EMS functions include resource monitoring, work-in-process (WIP) tracking, engineering data collection, quickly creating/adjusting process plans, timely material dispatching, and intelligent maintenance management. Using right, current, and accurate data (i.e., guaranteed and satisfied real-time responses) EMS will be capable of initiating and guiding all the plant floor manufacturing activities, responding to and reporting on them as they occur [5, 7]. 3. VIRTUAL PRODUCTION LINES IN EMS The concept of process routing has been used for many years. Whether traditional (make-toinventory) or current (make-to-market) manufacturing management systems, predefined process routes are the bible of production control for plants. When materials advance through different processing equipment, plant floor management uses these pre-defined routes to supervise, monitor, and control all the activities manually, semi-automatically, or automatically. Due to the dynamic changes of markets, production lines for products gradually become volatile. Instead of having lines defined exclusively before production, lines should be defined on the fly based on the dynamics of the plant floor and the priorities of ordered products. Once a product is ordered and scheduled for production, a corresponding production line will be strategically and optimally formed based on the status of plant floor manufacturing systems. As soon as the product gets finished, the line will be dismissed and all the equipment in the line will be optimally reallocated. This type of production line is logically volatile and thus called a Virtual Production Line (VPL) [10, 12]. From the production control perspective products advancing through a manufacturing system can be described by a product production flow diagram showing the sequence of product processing states on the plant floor (Fig. 3). Materials are released at the first processing step. The materials are processed as they progress through each successive processing machine by following designated process routes. As the materials exit from the last processing step they become finished products ready for shipping out [8]. Using the concept of VPL, the plant floor product flow diagram can be divided into multiple pieces. Each section of diagram covers the constituent equipment defined in a VPL. A VPL usually consists of a small subset of all the equipment on the plant floor. Therefore, a VPL-based EMS will consist of a number of EMS instances, where each EMS instance is instantiated with a piece of the product flow diagram and other relevant resource configurations. Fig. 5 shows the proposed VPL-based EMS structure model. VPL-based EMS is designed to allow production lines to be defined on the fly. When a product type is assigned, a VPL dedicated to making that type of product will be formed. Correspondingly, an instance of EMS will be spawned out. As soon as the product type is finished, the EMS instance governing the production line can be revised for a new type of product, or dismissed. The controlled equipment will be reassigned into a new VPL or other VPLs. When a VPL requires reconfiguration, equipment can be simply added or removed without affecting other VPLs. Different VPLs can share some critical processing machines [10]. In [12], algorithms have been developed for dynamically configuring VPLs based on different production control criteria.

5 270 Journal of the Chinese Institute of Industrial Engineers, Vol. 20 No. 3 (2003) Finished products exit. Material gets released. Material gets processed. Each node represents a processing machine. Materials advance through different processing equipment based on given routes and turn out as products as they exit from manufacturing systems. Figure 3. Graphical representation of manufacturing processes e-manufacturing System Equipment Controllers Product Type A Product Type C Product Type B Figure 4. Current EMS model e-manufacturing System Product Type A Equipment Controllers Product Type B Product Type C Figure 5. VPL-based EMS model

6 Robin G. Qiu: E-Manufacturing: the Keystone of a Plant-Wide Real Time Information System 271 An instance EMS governing a VPL can be running as a distributed computing process. The complexity of an EMS instance is substantially reduced compared to a monolithic and mammoth EMS [11]. This provides the opportunity for EMS to have real-time responses with satisfactory time resolutions. In addition, the VPL concept allows the dynamic modularization of both software and hardware. When a change, either adding a product type or deleting a product type, is required for a manufacturing system, only the relevant software and hardware modules are impacted, while the impact on the rest of the system is much limited [10]. 4. MANUFACTURING SYSTEMS AND SYSTEM INTEGRATIONS A typical manufacturing system consists of n processes. Materials will advance through some or all the processes on the plant floor before they are transformed to products. Normally a process plan or routing logic is given for a product, which is the guideline for all peoples involved in its management and production. As an example Fig. 6 shows a pilot Back-end semiconductor manufacturing system making ball grid array (BGA) products. In this pilot system there are 74 pieces of automated packaging and test equipment. Processes include wafer mounting, wafer cleaning, wafer sawing, die attach, cure, wire bonding, plasma cleaning, molding, mark, lead plating, trim, form, ball attach, singulating, encapsulation, seal, test, and inspection. Some operations are repeatable for a typical semiconductor product, for example cure, cleaning, and test. Different semiconductor products have different designs in terms of size, shape, and process requirements. Therefore process routing logic could be different from product to product. There are some very restricted requirements for how processes get executed in the Back-end of Semiconductor Manufacturing. For instance, products must be cured in Curing Ovens within 3 hours after dies are attached to the substrates. Otherwise, all the dies will be scraped. In order to guarantee that all the cure-ready products be delivered to Curing Ovens and placed into their chambers, a timely schedule should be made and the relevant tasks should be promptly assigned and executed. Thus a real-time response is essential. When thousands and thousands products are in production, the implementation of EMS with such real-time responses undoubtedly becomes extremely challenging. Figure 6. A pilot back-end semiconductor manufacturing system

7 272 Journal of the Chinese Institute of Industrial Engineers, Vol. 20 No. 3 (2003) EMS will be not functioning properly unless it can get machine, process, and material data from plant-floor equipment. Although there exists some industrial standards for building communication interfaces for equipment, the interface of the same type equipment from one vendor could be quite different from another vendor [6]. It is always true that there are some proprietary designs for equipment. The numerous variety of equipment installed in a manufacturing system thus make the system integration between all the equipment and EMS extremely difficult and challenging. It is also true that there is a lot of equipment having no communication interfaces available. Due to these two reasons it will be too costly to have EMS be physically integrated with all the production equipment on the plant floor. Currently most EMS s take client/server architecture. A server computer hosting all the EMS computations sits in a computer room, while many client computers reside on the plant floor. Users on the plant floor run the client applications to get instructions and record all the production data manually, semi-automatically, or automatically. When one process for a product lot is completed, the whole product lot will be moved into a waiting area and waiting for being delivered to the next process listed in the designated process routing logic. For each process, relevant information, such as process, product, consumables, and operator data should be recorded. Normally for unconnected equipment it is at user s discretion to decide when these data will be recorded, the product lots will be delivered, and the scheduled tasks will be executed [2]. Apparently, the plant floor information can t be guaranteed in real time as a whole. To make sure for EMS to get real-time information, it is necessary to have fine operation steps defined and information updates be enforced in the client applications for unconnected processes. Fig. 7 defines fine and necessary operations for them. In this generic process model five operation steps are defined. (Of course, even finer operations can be defined or customized in these individual steps [3].) They are Step 1. Delivery In a container with products is delivered into this process; Step 2. Move In the container with products is moved into the processing area; Step 3. Processing the products are being processed; Step 4. Move Out the container with products is moved out of the process; Step 5. Delivery Out the container with products is delivered into next process. Before an operation step is performed on an unconnected machine, it is required for a user to check the product status, equipment settings, or consumable parameters and record all the required data via the client application. When this operation step is done, the user has to continuously record all the relevant data. If any information were skipped from recording, it would be noticed as soon as next step gets started. By enforcing the checking of product and process status, equipment settings, and consumable parameters, all the plant-floor activities and information will be updated in EMS in real time. Accordingly, the office planning system will have real-time production information, so the prompt and optimal decisions can be made from the enterprise point of view Delivery In 2. Move In 3. Processing 4. Move Out 5. Delivery Out Figure 7. A generic process model

8 Robin G. Qiu: E-Manufacturing: the Keystone of a Plant-Wide Real Time Information System 273 EMS Server Database Office-Planning System EMS Instance EMS Instance Wireless EMS Terminal EMS Terminal EMS Terminal EMS RF Terminal : Equipment with or without communication capabilities Figure 8. An EMS framework 5. AN EMS SOLUTION Based on the proposed methodology an EMS solution has been implemented on the plant floor as the keystone of a plant-wide real-time information system. Fig. 8 shows this EMS framework, where applications are modularized across the network. To fully make use of the advanced technologies, such as Internet, Common Object Broker Request Architecture (CORBA), Distributed Common Object Model (DCOM), Personal Data Assistant (PDA), and wireless technologies, web-based architecture has been used for the development of such an e- Manufacturing system. The EMS server functions as the repository for functionality computations, algorithms, coordination, and system data management. An EMS instance is a computing process spawned out from the EMS server. An EMS instance governs only a few of VPLs defined in the EMS server. EMS terminals are EMS applications running on the plant floor. For those automation-ready machines, they are connected to EMS terminals; while other machines, human intervention becomes necessary, i.e., users supervise and conduct the defined processes by timely interacting with the EMS through EMS terminals. A group of equipment (either logical or physical) will have an EMS terminal. To improve the mobility of the EMS terminals, EMS clients can be running on either PDAs or radio frequency (RF) desktops. 6. CONCLUSIONS The manufacturing execution system has been improving the productivity of manufacturing systems since its emergence. A current manufacturing execution system can be evolutionarily promoted as an EMS by providing a plant-wide view of all the processes and products data with a much finer time resolution from the real-time perspective using the presented approach. Using current and accurate data (i.e., guaranteed and satisfied real-time responses) EMS effectively initiates and guides the entire plant floor manufacturing activities, optimally responds to and reports on them as they occur. As a result, EMS has successfully bridged the gap between the plant floor and office information systems; EMS is undoubtedly the keystone for a plant-wide real-time information system. REFERENCES 1. Baliga, J., MES and CIM: At the Center of Productivity, Semiconductor International, 8, (1998). 2. Camstar, MES Automation Amkor Technology IC Assembly, Camstar White Paper. 3. IBM, SiView Stardard, IBM Manufacturing and Information Web.

9 274 Journal of the Chinese Institute of Industrial Engineers, Vol. 20 No. 3 (2003) 4. MESA, Controls Definition & MES to Controls Data Flow Possibilities, MESA International White Paper Number 3 (2000). 5. MESA, MES Explained: A High Level Vision, MESA International White Paper Number 6 (1997). 6. Qiu, R. and D. Grant, Virtual Equipment Module a Generic Equipment Control Interface, The 14 th IFAC World Congress, (1999). 7. Qiu, R. and S. Joshi, "Structured Adaptive Supervisory Control Model and Software Development for a Flexible Manufacturing System," International Journal of Production Research, 38(1), (2000). 8. Qiu, R. and S. Joshi, Deterministic Finite Capacity Automata: A Solution to Reduce the Complexity of Modeling and Control of Automated Manufacturing Systems, Proceedings of the IEEE International Symposium on Computer-Aided Control Systems Design, , Dearborn, MI (1996). 9. Qiu, R. and S. Joshi, "A Structured Adaptive Supervisory Control Methodology for Modeling the Control of a Discrete Event Manufacturing System," IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 29(6), (1999). 10. Qiu, R. and R. Wysk, Design and Implementation of Virtual Production Lines for Discrete Automated Manufacturing Systems, The 14 th IFAC World Congress, (1999). 11. Rockwell, Making Sense of e-manufacturing: A Roadmap for Manufacturers, Rockwell Automation White paper. 12. Tang, Y., M. Zhou and R. Qiu, Design of Virtual Production Lines in Back-end Semiconductor Manufacturing Systems, IEEE International Conference on Systems, Man, and Cybernetics, , Nashville, Tennessee (2000). ABOUT THE AUTHOR Robin G. Qiu received the M.S. and B.S. degrees from Beijing Institute of Technology, Beijing, China, and the Ph.D. degree in Industrial Engineering with focus on Enterprise Information Systems and the Ph.D. (minor) in Computer Science from Pennsylvania State University, University Park, in He is currently a faculty member of Department of Information Sciences at Pennsylvania State University. He has more than 15 years of working experience in the field of information technology. He has had about 60 article published or presented in international journals or conferences. Dr. Qiu s research interests include Instant Information Retrievals (IIR) or Automatic Information Retrievals (Auto-IR), Component-based Software, Distributed Computing, Control and Management of Manufacturing Systems, and Enterprise Information Integration.