A.J.D. Lambert

Disassembly modeling for assembly, maintenance, reuse, and recycling

DISASSEMBLY PRACTICE Introduction Assembly and Disassembly History Levels of Aggregation Disassembly Optimization Basic Terminology Product Modeling Summary of the Chapters References Context of the End-Of-Life Disassembly Introduction Industrial Ecology Complex Products Complex Products Waste Breakdown Analyses of Some Prominent Complex Products Conclusion References The Disassembly Process Introduction The Product The Process Cost Metrics Revenue Metrics Economic Optimization Economic-Ecological (Eco-Eco) Models Example: Disassembly of Discarded Cars Conclusion References DISASSEMBLY SEQUENCING Disassembly Network Features Introduction Disassembly Process Representation Unconstrained Products Topologically Constrained Products Weakly Connected Products Geometrically Constrained Products Conclusion Appendices References Geometrical Constraints and Precedence Relationships Introduction Earlier Research on Precedence Relationships Bourjaults Method The Cut-Set Method A Moderately Complex Example m-Disassemblable Products Complex AND/OR Relationships Three-Dimensional Applications Disassembly Precedence Graphs Constrained Connection Diagrams Conclusion References Surface- and Direction-Oriented Analysis, and Modularity Introduction Product Representation and Classes Surface-Oriented Analysis Direction-Oriented Approach Interference Graphs Modularity Analysis Stability Analysis Force-Flow Analysis Conclusion References Selecting the Optimum Disassembly Sequence Introduction Sequence Independent Costs Sequence Dependent Costs, Heuristics, and Restricted Exact Methods Rigorous Exact Methods Demand-Dependent Problems Conclusion References DISASSEMBLY PLANNING Disassembly to Order Problems: Multi-Criteria Methods Introduction Multi-Criteria Methodologies Goal Programming Linear Physical Programming Conclusion References Disassembly Line Balancing Problems Introduction An Assembly Line Versus a Disassembly Line Balancing a Disassembly Line Description of the Disassembly Line Balancing Problem Heuristic and Metaheuristic Methods For Solving the DLBP Conclusion References

Determining optimum disassembly sequences in electronic equipment

This paper presents a study on disassembly sequence generation for electronic equipment. This is particularly useful because adequate end-of-life disassembly becomes crucial as take-back obligations are imposed for environmental reasons. Besides this, the hierarchical structure, typical to electronic products, makes product remanufacturing to an important topic. Methods from disassembly of mechanical assemblies are successfully adapted to these specific challenges.First, a modeling method for assemblies is described, which is aimed at automatically determining the optimum disassembly sequence. It is argued that the information, which is condensed in the connection diagram and the set of precedence relations, is sufficient for the automatic generation of such a sequence. Appropriate use of the precedence relations reduces the size of the model, that can be represented as an AND/OR graph with a restricted number of subassemblies and actions. With disassembly costs and revenues included, the optimum disassembly sequence can be found with standard linear programming software, thus without the need of visiting the complete search space. As a matter of fact, the size of the problem is strongly reduced, as it increases only linear with the number of parts in the assembly. It has been demonstrated that the model nearly instantaneously generates the optimum disassembly sequence. Besides this, the model can generate near optimum sequences as well, which is beneficial if multiple criteria are considered.

Demand-driven disassembly optimization for electronic products

In this paper, we address the problem of demand driven disassembly used to determine the optimal lot-sizes of end-of-life (EOL) products to disassemble so as to fulfil the demand of various components from a mix of different product types that have a number of components and / or modules in common. We discuss two approaches, viz., (1) the disassembly graph approach that is based on the study of the disassembly of mechanical products and (2) the component-disassembly optimization model that focuses on parts recovery by applying the reverse bill of materials. Although elegant, the main disadvantages of these two approaches are redundancy and nonlinearity respectively. To overcome these disadvantages, we propose a new method that combines the advantages of both approaches without their disadvantages. This is called the tree network model, which is a linear description of the demand driven, multiple product problem that includes commonality and multiplicity. Because of its simple structure, it can also be applied in dynamic situations, which is useful in problems that are related to production planning and inventory control in reverse logistics.

Environment conscious manufacturing

Industrial Metabolism: Roots and Basic Principles, A.J.D. Lambert Product Design for the Environment: The Life Cycle Perspective and a Methodological Framework for the Design Process, F. Giudice Product Lifecycle Monitoring via Embedded Sensors, S. Vadde, S.V. Kamarthi, S.M. Gupta, and I. Zeid Quantitative Decision-Making Techniques for Reverse/Closed-loop Supply Chain Design, K.K. Pochampally, S. Nukala, and S.M. Gupta Yesterday Proactive, Responsive Today: Use of Information to Enhance Planning in Closed Loop Supply Chains, M. Jalil, R. Zuidwijk, and H. Krikke Disassembly Line Balancing, S.M. McGovern and S.M. Gupta Multi-Kanban System for Disassembly Line, G. Udomsawat and S.M. Gupta Disassembly Sequencing Problem: Resolving the Complexity by Random Search Techniques, M. Tripathi, S. Agrawal, and M.K. Tiwari Human-in-the-Loop Disassembly Modeling and Planning, Y. Tang and M. Zhou Planning Disassembly for Remanufacture-to-Order Systems, K. Inderfurth and I.M. Langella Facility and Storage Space Design Issues in Remanufacturing, A. Topcu, J.C. Benneyan, and T.P. Cullinane Some Studies on Remanufacturing Activities in India, K. Mukherjee and S. Mondal Optimal Control Policy for Environmentally Conscious Manufacturing Systems, K. Nakashima Disassembly and Reverse Logistics: The Case of the Computer Industry, K.K. Dhanda and A. Peters Evaluating Environmentally Conscious Manufacturing Barriers with Interpretive Structural Modeling, J. Sarkis, M.A. Hasan, and R. Shankar

Optimizing disassembly processes subjected to sequence-dependent cost

Detection of the optimum disassembly sequence for a given product can proceed via mathematical programming, which is based on the AND/OR graph representation of its disassembly process. This is called the exact method for it reveals the global optimum. This paper describes an extension of the exact method in case sequence-dependent costs are considered. Previously presented methods confined themselves either to sequential disassembly, or were based on heuristics. The only exact method for the full problem known so far, needs an elaborate transformation of the AND/OR graph, and is based on integer linear programming. This paper discusses an alternate approach that uses a binary integer linear programming approach and that lacks the need of transforming the AND/OR graph. The proposed method is applied to arbitrary instances of some product structures that have been taken from the literature. Apart from this, the method is applied to an expandable AND/OR graph, that enables gradual increase of product complexity. It is demonstrated that the convergence of the iteration process is satisfactory, and the required CPU time appears comparatively small and only moderately increases with the number of constraints. It appears that the method applies to products with a complexity that cannot be managed with the integer linear programming model. The iterative method is promising for dealing with modularized products and as a benchmark for heuristic algorithms, which are used if products exhibit still higher complexity.

Methods for optimum and near optimum disassembly sequencing

This paper considers disassembly sequencing problems subjected to sequence dependent disassembly costs. In practice, the methods for dealing with such problems rely mainly on metaheuristic and heuristic methods, which intrinsically generate suboptimum solutions. Exact methods are NP-hard and therefore unsuitable to most of the practical problems. Nevertheless, it is useful to have exact methods available that can be applied in order to check, at least medium sized problems, to what extent the heuristically obtained solutions deviate from the optimum solution. The existing exact approaches, which are based on integer linear programming (ILP), become unmanageable, even for the cases of modest product complexity. To alleviate this problem to some extent, the iterative method that has been proposed by Lambert (2006) is applied here. This method is based on repeatedly solving a binary integer linear programming (BILP) problem instead of an ILP problem. The method appears to converge sufficiently quickly to be valuable for dealing with medium sized problems. We then use the iterative method for the validation of a new heuristic method that is also proposed in this paper. Finally, both the heuristic and the iterative BILP methods are implemented on a cellphone from practice consisting of 25 components that are represented, according to a set of precedence relationships, via a disassembly precedence graph.

Production planning for product recovery management

Production Planning and Control (PPC) in product recovery systems faces complications due to several characteristics which typically require tools different from, and in addition to, those known from traditional forward production and logistics systems (e.g., see Guide, 2000, and Inderfurth and Teunter, 2002). Many of these characteristics are due to additional specific operations necessary for disassembling, reprocessing, and rearranging recoverable products. Furthermore, in product recovery management, considerable sources of uncertainty have to be taken into consideration concerning the arrival of recoverables as well as the outcome of disassembly and reprocessing activities. The specific environment that poses challenges for PPC under product recovery will be demonstrated by two case examples, one of them concerning remanufacturing of used products in the field of discrete products’ manufacture, and the other considering rework of by-products in the field of process industries.

Optimal disassembly sequence generation for combined material recycling and part reuse

From graphical methods for optimal disassembly sequence generation, a new concept is applied based on mathematical programming. The method described enhances flexibility and offers the possibility of extension of the original problem. This paper discusses optimal disassembly sequence generation and illustrates some of its possibilities by considering an instructive case.

Generation of assembly graphs by systematic analysis of assembly structures

In assembly line balancing problems, parallel execution of assembly operations is often advocated because of its enhanced flexibility and minimum lead-time. Although the theoretical maximum number of possible assembly sequences combinatorially explodes with the number of components in a product, graphical representations can depict these sequences in a surveyable way. The AND/OR graph representation is an appropriate basis for optimum sequence selection, which can be achieved via heuristic, metaheuristic, and exact methods. The exact method, based on binary linear programming, is described. To arrive at the appropriate model, a novel approach for AND/OR graph generation, based on subassembly detection, is presented. The method is demonstrated with simple cases and next extended to increasingly complex products. A modification of the optimization method is applied, which enables a search for sequences with maximum parallelism.

Automatic determination of transition matrices in optimal disassembly sequence generation

This paper presents a method to automatically derive all the feasible sub-assemblies and transitions between them from assembly drawings. The method uses representation of the precedence relations via Boolean expressions. As a result, the transition matrix is automatically generated, representing the assemblys structure in the optimal disassembly sequence generation procedure. The method is applied to an assembly from industry.