A dynamic programming approach to integrated assembly planning and supplier assignment with lead time constraints

As manufacturers face fierce competition in the global market, responsiveness has become an important competitiveness factor in addition to quality and cost. One essential responsiveness strategy is to reduce product development and lead times by integrating assembly planning with supplier assignment. This paper addresses the problem of integrated assembly and supply chain design under lead-time constraints by formulating and solving an optimisation problem with minimal total supply chain costs. This new time-constrained joint optimisation problem belongs to an NP-hard resource-constrained scheduling problem. To model this problem effectively, we develop a novel Hyper AND/OR graph and apply it for integrating assembly and supply chain decisions. We also develop a dynamic programming model and associated algorithm in order to solve the integrated optimisation problem with pseudo-polynomial time complexity in practice. Numerical case studies validate that the methods developed can solve the integrated decision-making problem optimally and efficiently. This paper overcomes the limitations of previous studies on concurrent assembly decomposition and supplier selection, which optimises cost without time constraints. The models and results of this research can be applied to a variety of areas including assembly design, maintenance module planning and supply chain restructuring.     

Safety stock or safety lead time: coping with unreliability in demand and supply

Safety stock and safety lead time are common measures used to cope with uncertainties in demand and supply. Typically, these uncertainties are studied in isolated instances, ignoring settings with uncertainties both in demand and in supply. The current literature largely neglects case study based contexts and, often, single product situations are investigated in which machine set-ups are not considered. Based on the problems and findings in a case study, we investigate the effects of safety stock and safety lead time on delivery performance in a multi-product setting. The outcomes of the extensive simulation study indicate that utilising a safety lead time results in a higher delivery performance where there is a variable supply, whereas having a safety stock results in a higher delivery performance where there is unreliable demand information. In contrast to earlier findings in the single product situation, this study shows that managers facing the combination of unreliability in demand information and supply variability in a multiple product situation should opt for a safety lead time as the most effective way of improving their delivery performance.     

Applying data mining technique to disassembly sequence planning: a method to assess effective disassembly time of industrial products

Design for end-of-life and design for disassembly are enabling design strategies for the implementation of business models based on the circular economy paradigm. The paper presents a method for calculating the effective disassembly sequence and time for industrial products. Five steps support designers in defining liaisons and related properties and precedence among components with the aim to calculate the best disassembly sequence and time. The effective disassembly time is computed considering the actual conditions of a product and its components (e.g. deformation, rust and wear) using corrective factors. This aspect represents the main contribution to the state of the art in the field of design for disassembly. The corrective factors are derived from a specific data mining process, based on the observation of real de-manufacturing activities. The proposed approach has been used for calculating the disassembly times of target components in a washing machine and in a coffee machine. The case studies highlight the method reliability of both: definition of time-effective disassembly sequences and assessment of effective disassembly times. In particular, a comparison of experimental tests shows a maximum deviation of ?6% for the electric motor of the washing machine and ?3% for the water pump of the coffee machine.     

Cohesive Crack Model with Rate-Dependent Opening and Viscoelasticity: II. Numerical Algorithm, Behavior and Size Effect

In the preceding companion paper (Bažant and Li, 1995), the solution of an aging viscoelastic law was structure containing a cohesive crack with a rate-dependent stress-displacement softening law was reduced to a system of one-dimensional integro-differential equations involving compliance functions for points on the crack faces and the load point. An effective numerical algorithm for solving these equations, which dramatically reduces the computer time compared to the general two-dimensional finite element solution, is presented. The behavior of the model for various loading conditions is studied. It is shown that the model can closely reproduce the available experimental data from fracture tests with different loading rates spanning several orders of magnitude, and tests with sudden changes of the loading rate. Influence of the loading rate on the size effect and brittleness is also analyzed and is shown to agree with experiments. This revised version was published online in July 2006 with corrections to the Cover Date.