The goal of this research in environmentally responsible product design is to enable design for remanufacture. Remanufacture is a production-batch process of disassembly, cleaning, refurbishment and replacement of parts in products that are worn, defective or obsolete. By recycling at the parts level, remanufacturing preserves the valued added to the part during manufacture. Furthermore, remanufacture postpones the eventual degradation of the raw material due to contamination and molecular breakdown, frequently characteristic of scrap-material recycling. The production-batch nature of remanufacturing enables it to salvage functionally failed but repairable products that are discarded due to high labor costs associated with individual repair.

Insights on how products can be designed to facilitate remanufacture were gained through collaboration with three companies that remanufacture different products. The most essential aspect of design for remanufacture was revealed to be in conflict with other prevalent design-for-x methodologies, such as design for assembly and design for recycling. Design for remanufacture was therefore viewed in the context of other design-for-x methodologies. The domains selected for simultaneous consideration were manufacture and assembly, maintenance, remanufacture, and scrap-material recycling. Since fastening and joining issues are common to all these domains, a framework that evaluates the effect of joint design on each of these life-cycle stages was developed. This framework was applied to case studies of joints that did not facilitate remanufacture to estimate the cost of remanufacture relative to other life-cycle costs determined by the joint design.

These case studies identified the importance of reliability modeling for remanufacture. A probabilistic reliability model was developed to describe the effect of remanufacture on the reliability of parts and systems. The basic behavior of this model, which simulates the replacement of failed parts with parts of the same type, was experimentally verified. The model was further developed to accommodate the common practice of system modification during remanufacture. The various inputs to this reliability model are factors that can be combinatorially optimized to minimize life-cycle cost. The optimization of life-cycle fastening and joining costs using genetic algorithms was implemented.