Design of a Web-based Decision Support System for End-of-Life Vehicles Hui Cao Computer Integrated Manufactory Research Unit (CIMRU) National University of Ireland, Galway Galway, Ireland
[email protected] December, 2005
ABSTRACT Decision Support Systems (DSS) have been involved in all of the stages of the products life-cycle. In the business of end-of-life vehicles (ELVs) treatment, once PEID (Product Embedded Information Devices) systems are used to collect all life-cycle data of the vehicles, a DSS could be needed to manipulate the information and help the operator optimizing the decision results during the treatment. In this paper, a Web-based DSS for ELVs is designed based on the infrastructure of PROMISE project. Its decision flow and the system structure are also presented.
Keywords Decision Support Systems; Web-based; End-of-Life Vehicles
1. INTRODUCTION Since the information flow breaks down after the delivery of the product to the customer and becomes less and less complete from the MOL phase to the final EOL scenario, the objective of PROMISE (PROduct lifecycle Management and Information tracking using Smart Embedded systems) is to develop a new generation of product information tracking and flow management system and close the loop of information flow. The project devotes itself to developing new IT infrastructure and ubiquitous PLM software using the technologies of Product Embedded Information Devices (PEID), wireless communication, etc. With integration of PEID systems into the internal components of the vehicles, the vehicle producers, maintainers, and dismantlers have the possibility of tracking the vehicles over its entire lifecycle and getting the information of its design, production, usage, maintenance and recovery, thus enabling the closure of the PLM information loop. Having this information, a web-based DSS can be implemented to support the removal and the recovery decision for end-of-life vehicle (ELV) dismantlers, collect the life-cycle information at the end-of-life (EOL) stage, and storage it to the Product Data Knowledge Management (PDKM) System to close the information flow.
2. DECISION SUPPORT SYSTEMS 2.1 DSS in General The original DSS concept was introduced by Gorry and Scott Morton in the early 1970s. They defined Decision Support Copyright held by the author.
Systems as “Interactive computer-based systems, which help decision makers utilize data and models to solve unstructured problems”[11]. Actually, DSS is taken as an umbrella term to describe any computer-based information system used to support decision making in an organization[11]. In the past three decades, DSS have evolved significantly from the original simple text-interface programs supporting individual decision-makers, to friendly graphic-interface systems helping workgroups and teams. From the early 1990s, four powerful tools have been engaged in DSS development: data warehousing; online analytical processing (OLAP); data mining; and the technology associated with the World Wide Web[9]. With the emergence and development of the World Wide Web (WWW) and internet technologies, researchers were exploring the possibilities for the next generation of DSS by the mid-1990s. The internet brings a revolution in the ways of information spreading and exchanging, and the Web environment is emerging as a very important DSS development and delivery platform. Web-based DSS have reduced technological barriers and made it easier and less costly to make decision-relevant information available to managers and staff users in geographically distributed locations [9]. Currently, DSS facilitate a wide variety of decision tasks including information gathering and analysis, model building, sensitivity analysis, collaboration, alternative evaluation, and decision implementation[1]. In the industrial area, DSS have been involved in all the phases of products life-cycle: Begin-of-Life (BOL), Middle-of-Life (MOL), and End-of-Life (EOL). Decisionmaking involved in the BOL phase include product design, production planning, process control, etc. In the MOL phase, DSS are applied to assist product maintenance, diagnoses, and prognoses. The products are collected, recovered or disposed in their EOL stage. Some examples of DSS practiced in the EOL phase include Boyle and Baetz [3] described a knowledge-based decision support system which would assist managers in determining waste management options for all types of wastes from one or more industrial plants, giving priority to sustainable use of resources, reuse and recycling. Masanet [6] introduced the Take-Back Planning Advisor, a decision-support tool for the environmental and economic planning of take-back systems for plastic components from end-of-life electronics. And Bhargava and Tettelbach [2] presented a web-based decision support system for managing the logistics issues for waste collecting and transporting.
2.2 Software tools for Web-based DSS development DSS tools started in the DOS and UNIX environments around the late 1970s and then moved to Windows in the early 1990s [9]. According to Bhargava [1], Web technologies can be classified in terms of those technologies that enable (1) server-side computation, (2) client-side computation, and (3) a distributed implementation and deployment of DSS components. Before server pages (ASP, PHP, and JSP) were introduced to the world, CGI took a great place in web-based DSS development. Currently two primary frameworks that can be used to develop web-based DSS are Microsoft’s .Net and Sun Microsystems’s J2EE. According to Kwon [5], Microsoft views the benefits of web services as threefold: enabling best-of-breed business integration, providing a resilient and scalable platform, and enabling freedom of choice in transports and encoding protocols. Chen [4] discussed an architecture and design of Web-based GDSS, and implemented it in ASP.Net using Visual Basic.Net. On the java side, Ray [7] developed a web-based spatial decision support system using J2EE web-architecture for managing the movement of oversize and overweight vehicles over the State’s highways. Wang [12] presented an agent-based decision support system for securities exception management using JWSDP (Java Web Services Development Package), which brings together a set of Java APIs for XML-based Java applications by supporting key XML standards such as SOAP (Simple Object Access Protocol), WSDL (Web Services Description Language) and UDDI (Universal Description and Discovery Interface) 1 . JSP (JavaServer Pages), JNDI (Java Naming Directory Interface) and JDBC (Java Database Connectivity) was used by Silva [10] to develop a web-based DSS for mould industry named MAPP (Mould: Assistant Production Planner).
Auto Recyclers Trading System (PARTS)2. The Pinnacle system offers decision support at each stage of the collection and processing of the ELV. It can receive instant feedback of the ELV information from the tow driver and generate a dismantling check sheet based upon the vehicle’s information, stock levels, legislation, etc. The system uses the ABC classification method to grade the quality of the parts according to the hours needed for repair. Also, a pricing module is involved in the system to aid the removal decision, and the inventory module is used to enhance the inventory process in the Pinnacle System. Another generalized removal decision support system is UCars3 software, which examines the decision problem from a financially-oriented standpoint focused upon the car-level rather than the part level.
4. SYSTEM STRUCTURE 4.1 Decision Flow The decision support for ELVs in the PROMISE demonstrator consists of two process stages (Figure 1). In the first stage (remove decision), the system generates a bill of material (BOM) of the car automatically according to the car model or identity number inputted and the background database. Then the decision maker can judge the destiny of the components (remove from the vehicle for further treatment, or leave on the vehicle to be shredded) one by one considering the legislation, quality, cost and market (Figure 2) with the help of DSS.
3. DECISION SUPPORT IN ELV An end-of-live vehicle (ELV) is a vehicle to be processed by dismantling, depollution, reuse or remanufacturing of parts, shredding, recycling to material, energy recovery, disposal to landfill, etc. According to EU legislation (EU Directive 2000/53), the recycling/recovery rates of all ELVs will have to achieve 85% in terms of weight by 2006, and up to 95% by 2015 [8]. In order to achieve these targets, when the dismantler receives an ELV, they have to face a set of decisions; for example, which parts should be removed from the vehicle; how to recovery (reuse or remanufacture) the removed parts; which customers would the parts be delivered to; and where to store the parts. Large amounts of information is needed in order to optimize these decisions, and computerized systems like DSS make it possible to consider the various aspects of the decision-making processes, such as legislation, environment, cost and effectiveness. Although ELV dismantling is a well established business, currently there are very few computer systems that allow the removal decision support, that is, the decision to remove individual components from the ELV. One example is PinnacleTM
Figure 1: A schematic view of DSS for ELVs In the second stage, the system focuses on the recovery path of the removed components. With the PEID data read from the component, the system and operators would master all the lifecycle information of the components including design, production, usage and maintenance. Using this information the DSS can help the decision maker find the optimal (or at least good enough) 2
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http://developers.sun.com/sw/building/tech_articles/overview_so ap.html
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http://www.actual-systems.com/page.php?stylesheet=stylesheet/ main.css&content=pinnacle http://www.ucars.com.au/prodinfo.htm
recovery method (reuse, remanufacture, or recycling) for the component. Once the recovery method issued, the system will cooperate with its backend systems to suggest the downstream customer and storage position for the component.
6. ACKNOWLEDGMENT The author wishes to acknowledge the European Commission and the PROMISE consortium for their support. Especially, I am very grateful to Paul Folan in CIMRU, who advises and collaborates a lot in the work and reviewed and discussed a draft of this paper.
7. REFERENCES [1]
Figure 2: Make removal decision process
4.2 System Architecture Shim [9] believed that classic DSS tool design was comprised of 3 components: database management system, model management system and user interface. In the PROMSE ELV demonstrator, a Web-based Decision Support System will be implemented based on the J2EE platform. Decision-makers will interact with the system through web pages generated by JavaServer Pages (JSP) or Servlets. A set of Enterprise Java Beans (EJBs) can be implemented to deal with decision models and manipulate database via Java Database Connectivity (JDBC).
5. CONCLUSION An optimal scenario to close the information loop which breaks down nowadays in product’s MOL and EOL phases is to implement PEID systems for the product. Thus it will bring huge amounts of information waiting for processing in the EOL stage of the product. A decision support system can be used to collect and manipulate the data and help the decision maker finding an optimal component recovery solution depending on the information on the PEIDs in the ELVs. The DSS designed in this paper would confront with a few of problems before it can be implemented in next stage, e.g. the reading, process, and transfer method of the PEID data at the client, the decision making criteria, to name but a few.
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