VOL. 11, NO. 10, MAY 2016 ISSN 1819-6608 ARPN Journal of Engineering and Applied Sciences © 2006-2016 Asian Research Publishing Network (ARPN). All rights reserved. www.arpnjournals.com 6428 THE IMPROVEMENT OF LINE EFFICIENCY ON DISASSEMBLY LINE BALANCING PROBLEM: AN HRRCD’S HEURISTIC RULE Yeoh Kim Hao and Sulaiman Hasan Department of Manufacturing and Industrial Engineering, Universiti Tun Hussein Onn, Malaysia E-Mail: kh.yeoh@hotmail.com ABSTRACT Disassembly line balancing problem (DLBP) is the factor of remanufacturing industry to improve their effectiveness on part demand. The application of HRRCD’s (Hazard-Reuse-Recycle-Collected-Disposed) heuristic rule will solve the problem of disassembly line by improving the line efficiency and reducing balance delay. A case study from truck’s remanufacturing industry will apply the heuristic rule, which it will improve disassembly line efficiency and decline idle time. Observation from real truck disassembly line will apply in time study and the results show that HRRCD based disassembly line balancing method is the best method to optimize the truck’s disassembly line. Keywords: disassembly line balancing problem, remanufacturing, line efficiency, idle time. INTRODUCTION Remanufacturing is an industrial process in which worn-out products are restored to like-new product’s conditions. Thus, remanufacturing provides the quality standards of new product with used parts (McGovern and Gupta, 2003a). In order to minimize the amount of waste sent to landfills, product recovery seeks to obtain materials and component from old or outdated products through recycling and remanufacturing. This includes the reuse of components and products. There are many attributes of a product that enhance product recovery such as ease of disassembly, modularity, type and compatibility of materials used, material identification markings, and efficient cross-industrial reuse of common parts/materials. The first crucial step of product recovery is disassembly (McGovern and Gupta, 2004a). Recently, disassembly has gained a great deal of attention in the literature due to its role in product recovery. A disassembly system faces many unique challenges; for example, it has significant inventory problems because of the disparity between the demands for certain parts or subassemblies and their yield from disassembly. The flow process is also different. As opposed to the normal “convergent” flow in regular assembly environment, in disassembly the flow process is “divergent” (a single product is broken down into many subassemblies and parts). There is also a high degree of uncertainty in the structure and the quality of the returned product. The conditions of the products received are usually unknown and the reliability of the components is suspects. Some parts of the product may cause pollution or may be hazardous. These parts tend to have a higher chance of being damaged and hence may require special handling, which can also influence the utilization of the disassembly workstations. For example, an automobile slated for disassembly contents a variety of parts that are dangerous to remove and/or present a hazard to the environment such as the battery, airbags, fuel and oil. Various demanded sources may also lead to complications in disassembly line balancing. The reusability of parts creates a demand for these parts, however, the demands and availability of the reusable parts is significantly less predictable than what is found in the assembly process. Finally, disassembly line balancing is critical in minimizing the use of valuable recourses (such as time and money) invested in disassembly and maximizing the level of automation of the disassembly and the quality of the parts (or material) removed (McGovern and Gupta, 2003a). DISASSEMBLY LINE BALANCING Introduction of disassembly line balancing The basic disassembly line balancing problem (DLBP) can be stated as the assignment of disassembly tasks to an ordered sequence of stations such that various forms of precedence relations are satisfied and some measure of effectiveness is optimized. Due to long term effect of the balancing decisions, the objective has to be chosen carefully considering the strategic goals of the enterprise (Becker and Scholl, 2003). Commonly studied objectives include minimizing number of stations given cycle time, maximizing production rate (equivalently minimizing cycle time) given number of stations, maximizing the line efficiency (directly depends on the number of stations and cycle time, cost minimization and profit maximization. Profit seeking nature of disassembly systems should be taken into consideration in choosing the objective for DLBP. Mathematical model of disassembly line balancing According to McGovern and Gupta (2011), the mathematical foundations for the research of the Disassembly Line Balancing Problem (DLBP) have been discussed and then each of these is generated using formulae. These formulae are essential in enabling line efficiency analysis with proposed HRRCD heuristic rule. The formulae to calculate Workstation Idle Times as below: