A green productivity model for manufacturing processes using life cycle assessment and analytic hierarchy process

• Main Author: Henson, Ruby P.
• Format: text
• Language: English
• Published: Animo Repository 2005
• Subjects: Manufacturing processes; Process control; Assembly-line methods; Production engineering; Industrial Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_doctoral/79; https://animorepository.dlsu.edu.ph/context/etd_doctoral/article/1078/viewcontent/CDTG003846_P.pdf
• Institution: De La Salle University

There is an increasing awareness of issues related to sustainable development and environmental considerations are becoming a source of competitive advantage for industries in the global market. Many concepts and strategies in improving product and process performance have evolved over time from the interaction of environmental and resource parameters in product development, process technology, and systems management. Green Productivity (GP), a new paradigm in sustainable manufacturing, integrates environmental protection and productivity where the former serves as the foundation for sustainability and the latter, the framework for continuous improvement (APO, 2000). This productivity approach to the sustainability of industries requires the adoption of cleaner production techniques and the development of appropriate indicators and instruments to measure economic and ecological efficiency or ecoefficiency (WBCSD, 2001). The study presents a methodology for the GP diagnosis of manufacturing processes that integrates life cycle assessment (LCA) and the analytic hierarchy process (AHP). LCA sets the goal of the systems analysis methodology that includes inventory, impact and improvement assessment from which the decision parameters are scoped out. The AHP provides the decision framework and the valuation tool in impact and improvement assessment to obtain priority weights for decision making leading to systematic improvement along the product life cycle. An input-output material flow analysis serves as the basis of the indicator system for GP performance measurement in the scenario analysis. The diagnostic model was applied on a semiconductor assembly/packaging operation. From the streamlined life cycle inventory, the significant impact factors derived were water resource depletion (WRD), energy resource depletion (ERD), human toxicity3 air (HTA), human toxicity-land (HTL), human toxicity-water (HTW), aquatic ecotoxicity (ETA) and terrestrial ecotoxicity (ETT). Valuation of impact factors using the AHP prioritized ETT, HTL, WRD and ERD in The AHP procedure also prioritized material-based and process-based techniques for GP improvement. In the scenario analysis, the highest values in GP improvement indices were noted for energy utilization, water utilization and terrestrial ecotoxicity with the implementation of a process-based improvement technique on a product-specific operation. Expert system technology was explored in developing a diagnostic prototype that emulates how human experts diagnose green productivity of manufacturing processes. Using CLIPS (C Language Integrated Production System), rule-based knowledge processing is made on the parameters derived from the application of the LCA-based model to generate the diagnostic interpretation and advice on the priority weights for the impact factors and improvement options obtained using the analytic hierarchy process and green productivity assessment based on performance indicators. The study also demonstrated the viability of merging database management system with expert system technology into an intelligent decision support system for GP assessment of manufacturing performance.