Planning product disassembly for material recovery opportunities

This paper addresses an increasingly important aspect of product design and its relationship to life-cycle costing: disassembly for material recovery opportunities (MRO). MRO is defined as an opportunity to reclaim post-consumer products for recycling, remanufacturing and re-use. The authors have developed a methodology which can be used to identify and assess cost-effective characteristics of disassembly for the recovery of products. The central focus of this paper is aimed at improving the efficiency of the disassembly planning process and generating an optimal disassembly sequence. Four criteria are established to optimize the generation of the disassembly sequence: (1) material compatibility, (2) clustering for disposal, (3) concurrent disassembly operations, and (4( maximizing yield. In this paper we define the ‘disassemblability’ of a product as the ability to optimize the design and disassembly process for removal of specific pans or materials in a manner which will minimize costs. Steps have been taken to incorporate this methodology within a life-cycle analysis software tool (EDIT) to be used at the early concept stage of product design.     

A precedence-constrained asymmetric traveling salesman model for disassembly optimization

In this paper, we address a product-disassembly optimization problem, which aims at minimizing the costs associated with the disassembly process (namely, the cost of breaking the joints and the sequence-dependent set-up cost associated with the disassembly operations), while maximizing the benefits resulting from the recovery of components and subassemblies that constitute the product. A method able to capture the mating relationships among the parts and joints of the product through a network representation scheme is developed. The disassembly optimization problem is formulated as a precedence-constrained asymmetric traveling salesman problem. A three-stage iterative procedure is designed to obtain optimal or near-optimal solutions to the problem. The results demonstrate that our procedure generates solutions that are within 2% of optimality for all test cases, while only requiring a reasonable computational effort.     

An analysis of manufacturers’ supply and demand uncertainty based on the dynamic customisation degree

Diverse demands regarding products are common; however, manufacturers usually cannot respond immediately to meet such changes upon demand, and thus, customer satisfaction tends to be reduced. Notebook computer manufacturers adopt a production mode of mass customisation; hence, a certain degree of dynamic customisation measurements, inherent in different supply chain models, allow manufacturers to evaluate costs and profits in advance. The application of the model, as proposed in this study, indicates that the most important factor of the customisation degree is product price. The dynamic customisation degree is adjusted based on monitoring indicators, which requires less total cost and produces greater accuracy in forecast results regarding the prediction model of customer demands. This study develops a dynamic customisation model for total product profits, inventory cost of semi-manufactured products, shortage costs and buffer inventory costs, which are affected by the degree of dynamic customisation of the products. It also analyses the supply and demand uncertainties of the Direct Shipment of the Manufactured Model, as well as the Door-to-Door Direct Shipment of the End User Model in the notebook computer industry, as the criteria with respect to a firm's customisation degree, costs, and profits in different supply chain mode operations.     

Selective disassembly sequencing with random operation times in parallel disassembly environment

Selective disassembly sequencing is the problem of determining the sequence of disassembly operations to extract one or more target components of a product. This study considers the problem with random operation times in the parallel disassembly environment in which one or more components can be removed at the same time by a single disassembly operation. After representing all possible disassembly sequences using the extended process graph, a stochastic integer programming model is developed for the objective of minimising the sum of disassembly and penalty costs, where the disassembly costs consist of sequence-dependent set-up and operation costs and the penalty cost is the expectation of the costs incurred when the total disassembly time exceeds a threshold value. A sample average approximation-based solution algorithm is proposed that incorporates an optimal algorithm to solve the sample average approximating problem under a given set of scenarios for disassembly operation times. The algorithm is illustrated with a hand-light case and a large-sized random instance, and the results are reported.     

Selection of management accounting systems in Just-In-Time and Theory of Constraints-based manufacturing

In today's competitive business environments, a firm's long-term survival rests heavily on its ability to sustain manufacturing superiority over its competitors. To provide the firm with detailed guidelines for sustaining manufacturing superiority, this paper examines the impact of different management accounting systems, manufacturing control systems and time horizon on manufacturing performance in an enterprise resource planning integrated environment. These management accounting systems include traditional costing, activity-based costing and throughput accounting. The manufacturing control systems include Just-In-Time- and Theory of Constraints-based manufacturing. Through a series of simulation experiments, it was found that activity-based costing provided higher short- and long-term profit, better customer service and lower work-in-process inventory than traditional costing and throughput accounting in situations where firms have high overhead costs and relatively low labour and material costs, while carrying ending inventories because of demand uncertainty. Traditional costing also outperformed throughput accounting by exploiting the real-time information sharing capabilities of an enterprise resource planning system. Just-In-Time manufacturing outperformed Theory of Constraints with respect to short- and long-term profitability, customer service, and work-in-process inventory because of differences in buffer inventory policies and sequencing rules. However, time horizon and its interaction with management accounting systems had no impact on the manufacturing performance. In addition, the results suggest that a management accounting system that depicts the manufacturing process tended to provide more accurate product cost information and resulted in a better system performance than the others.     

Heuristic algorithms for minimising total recovery cost of end-of-life products under quality constraints

Recently, the optimisation of end-of-life (EOL) product recovery processes has been highlighted. At the inspection phase after disassembly, each part can have various recovery options such as reuse, reconditioning, remanufacturing, and disposal. Depending on the selected options of parts, the values of recovered products that are made by reassembling parts will be different. Hence, it is important to decide appropriate recovery options of parts at the treatment of EOL products, in order to maximise the values of recovered products. To this end, this study deals with a decision making problem to select the best recovery options of parts for minimising the total recovery cost of products under quality constraints. This problem is formulated with a mixed integer nonlinear programming model and heuristic search algorithms are proposed to resolve it. A case study for a turbocharger product is introduced with computational experiments of the proposed algorithms.     

Simultaneous use of customer,product and inventory information in dynamic product promotion

Currently, retail data are both accessible and plentiful while the retail space has become increasingly competitive. When combined with technology like mobile computing and low cost analytic techniques, data can now be leveraged by companies to dynamically offer individualised promotions in real time. This paper considers the relative value of three retail information elements which can be used by retailers to dynamically identify a subset of product offerings to promote to their customers. The retail information elements considered are: (a) product markup, (b) customer preference estimates gleaned from purchase history and (c) retailer inventory positions. The importance of each element is evaluated singularly and in combination as is their effect on promotion success, inventory costs and average markup. Computational results show that, on average, dynamic promotion policies incorporating all retail information elements can increase expected profit by 14.5% over policies that consider only customer preference and by 8.4–9.1% over policies that consider only product margin or inventory. Results demonstrate that customer preference information alone does little to improve performance but provides substantial synergistic benefits when combined with either inventory or markup information elements. The most information intensive dynamic promotion policy is then extended to include price as a decision variable.     

Economical evaluation of disassembly operations for recycling,remanufacturing and reuse

This paper introduced a procedure which integrates economical factors into the scheduling of disassembly operations for Material Recovery Opportunities (MRO). MRO are defined as opportunities to reclaim post-consumer products for recycling, remanufacturing and reuse. Traditionally, recyclers have resorted to using heuristics for analysing the breakdown of products and the associated costs. In this paper, a quantitative method of disassembly analysis is developed. Its aim is to improve the efficiency of the disassembly planning process and to generate an optimal disassembly sequence which maximizes profit. Three economic indices are used to evaluate the trade-off between reclamation and disposal of individual components. A systematic procedure of generating an optimal disassembly sequence based on maximizing the profits of material recovery is presented. Three criteria are established to reduce the search space and facilitate recovery opportunities: (1) material compatibility, (2) clustering for disposal, and (3) concurrent disassembly operations. An example is provided on a product being disassembled for recycling at a local recycling plant in Canada.     

Disassembly line balancing using linear physical programming

Disassembly is the separation of a product into its constituent parts in a systematic way. It has gained importance recently due to its vital importance in product recovery. Cost-effective implementation of disassembly operation has a direct impact on the profitability of product recovery activities (recycling, remanufacturing etc.). Although it is possible to carry out disassembly operations in a disassembly station or in a disassembly cell, the highest productivity is achieved in a disassembly line. The output of a disassembly line can be maximised only if the line is balanced. A linear physical programming-based disassembly line balancing method is proposed in this study. This method was used to balance a mixed-model disassembly line and the effectiveness of the method was illustrated by analysing the results.     

Scheduling on a bottleneck station: A comprehensive cost model and heuristic algorithms

This paper presents a mathematical model for scheduling a single processor system to minimize aggregate operations cost consisting of inventory holding cost, opportunity cost due to the delay in realization of revenue, inflationary spiral effect, and the time value of money on costs yet to be incurred. We propose a number of heuristic algorithms for solving the model and provide extensive numerical experiments. Computational results are reported.     

Cyclic lot scheduling with sequence-dependent set-ups: a heuristic for disassembly processes

The importance of material and product recovery is steadily increasing, mainly due to customer expectations and take-back obligations. Disassembly is a major operation in material and product recovery, since returned products are often disassembled to separate materials and components. The paper considers the problem of scheduling several items on a single disassembly facility. It develops a cyclic lot-scheduling heuristic for disassembly processes with sequence- dependent set-ups, resulting in disassembly frequencies for the items. Additionally, the way the problem is formulated allows calculation of the profitable use of the facility. The disassembly frequencies and the profitable use of the facility are used to create a cyclic schedule.     

Minimizing response time in a two-stage supply chain system with variable lead time and stochastic demand

We consider customer response time minimization in a two-stage system facing stochastic demand. Traditionally, the objective of representative mathematical models is to minimize costs related to production, inventory holding, and shortage. However, the highly competitive market characterized by impatient customers warrants the inclusion of costs related to customer waiting. Therefore we investigate a supply chain system in an uncertain demand setting that encompasses customer waiting costs as well as traditional plant costs (i.e. production and inventory costs). A representative expected cost function is derived and the closed form optimal solution is determined for a general demand distribution. We also provide examples to illustrate results for some common probability distributions. Our results indicate significant cost savings under certain assumptions when comparing solutions from the proposed model to the traditional newsvendor order/production quantity.     

Single-item production–delivery scheduling problem with stage-dependent inventory costs and due-date considerations

This paper studies an integrated scheduling problem for a single-item, make-to-order supply chain system consisting of one supplier, one capacitated transporter and one customer. Specifically, we assume the existence in the production stage of an intermediate inventory that works as a buffer to balance the production rate and the transportation speed. Jobs are first processed on a single machine in the production stage, and then delivered to the pre-specified customer by a capacitated vehicle in the delivery stage. Each job has a due date specified by the customer, and must be delivered to the customer before its due date. Moreover, it is assumed that a job that is finished before its departure date or arrives at the customer before its due date will incur a stage-dependent corresponding inventory cost (WIP inventory, finished-good inventory or customer inventory cost). The objective is to find a coordinated production and delivery schedule such that the sum of setup, delivery and inventory costs is minimised. We formulate the problem as a nonlinear model in a general way and provide some properties. We then derive a precise instance from the general model and develop a heuristic algorithm for solving this precise instance. In order to evaluate the performance of the heuristic algorithm, we propose a simple branch-and-bound (B&B) approach for small-size problems, and a lower bound based on the Lagrangian relaxation method for large-size problems. Computational experiments show that the heuristic algorithm performs well on randomly generated problems.     

Optimal production operations sequencing

The goal of this research is to address the following issues: Under what circumstances should a company perform operations resequencing? Which design leads to the most desirable inventory cost and customer service trade-off? For make-to-stock production–inventory systems with no WIP safety stocks, we establish the optimal production operations sequencing and determine easy-to-use criteria for resequencing when technologically possible. We show that in many cases, resequencing decisions can be made using a graphical decision tool, namely cost–time profiling. For more complex systems with work-in-progress safety stock inventories, we analyze how system attributes drive overall performance. Some specific resequencing opportunities are examined in terms of their effects on cost and on the levels of optimum safety stocks.     

Dynamic analysis and design of a semiconductor supply chain: a control engineering approach

The combined make-to-stock and make-to-order (MTS-MTO) supply chain is well-recognised in the semiconductor industry in order to find a competitive balance between agility, including customer responsiveness and minimum reasonable inventory, to achieve cost efficiency while maintaining customer service levels. Such a hybrid MTS-MTO supply chain may suffer from the bullwhip effect, but few researchers have attempted to understand the dynamic properties of such a hybrid system. We utilise a model of the Intel supply chain to analytically explore the underlying mechanisms of bullwhip generation and compare its dynamic performance to the well-known Inventory and Order-Based Production Control System (IOBPCS) archetype. Adopting a control engineering approach, we find that the feedforward forecasting compensation in the MTO element plays a major role in the degree of bullwhip and the Customer Order Decoupling Point (CODP) profoundly impacts both the bullwhip effect and the inventory variance in the MTS part. Thus, managers should carefully tune the CODP inventory correction and balance the benefit between CODP inventory and bullwhip costs in hybrid MTS-MTO supply chains.     

Mathematical model and solution algorithms for selective disassembly sequencing with multiple target components and sequence-dependent setups

This study considers selective disassembly sequencing under the sequential disassembly environment in which one component is obtained at each disassembly operation. The problem is to determine the sequence of disassembly operations to obtain multiple target components of a used or end-of-life product for the purpose of repair, reuse, remanufacturing, disposal, etc. In particular, we consider sequence-dependent setups in which setup costs depend on the disassembly operation just completed and on the operation to be processed. The problem is represented as a disassembly precedence graph and then a new integer programming model is suggested for the objective of minimising the total disassembly cost. After it is proved that the problem is NP-hard, we suggest two types of heuristics: (1) branch and fathoming algorithm for small-to-medium-sized instances; and (2) priority-rule-based algorithm for large-sized instances. A series of computational experiments, i.e., effectiveness of the new integer programming model and performances of the two heuristic types, were done on various test instances, and the results are reported. In addition, to show the applicability of the mathematical model and the solution algorithms, a case study is reported on an end-of-life electronic calculator.     

Dynamic disassembly planning for remanufacturing of multiple types of products

With the increased need for remanufacturing of end-of-life products, achieving economic efficiency in remanufacturing is urgently needed. The purpose of this study was to devise a cost-minimisation plan for disassembly and remanufacturing of end-of-life products returned by consumers. A returned end-of-life product is disassembled into remanufacturable parts, which are supposed to be used for new products after being remanufactured. Each end-of-life product is disassembled into parts at variable levels and through variable sequences as needed, taking into account not only disassembly but also manufacturing, remanufacturing, and holding inventory of remanufacturable parts. This study proposes a mixed integer linear programming (MILP) model for derivation of the optimal disassembly plan for each returned product, under deterministically known demand and return flows. For the purposes of an illustrative example, the proposed model was applied to the formulation of an optimal disassembly and remanufacturing plan of ‘fuser assembly’ of laser printers. The solution reveals that variable-level disassembly of products saves a significant remanufacturing cost compared with full disassembly.     

A lateral transshipment model for perishable inventory management

Since inventory costs account for half of logistics costs, optimal inventory management to minimise total inventory costs remains a sustainable competitive advantage. Lateral transshipment (LT) is evidently a proven strategy to minimise total inventory costs. The additional LT costs are more than compensated by lowering the stock-out costs. Previous LT models have not been applied to perishable products. Our proposed LT model embodies spoilage costs in the total inventory costs function with the other cost components (purchase from a regular supplier, LT, backordering and holding), and optimises the trade-off among these five key cost components. Numerical examples from a supermarket chain case study demonstrate that, as compared against the no or lower spoilage costs scenarios, lower LT costs are required to trigger the decision point for implementing LT in the higher spoilage costs scenario. However, common to both the with and without spoilage costs scenarios, LT is still the preferred strategy to minimise total inventory costs, given the decision rules are satisfied.     

Joint production and shipment lot sizing for a delivery price-based production facility

A joint economic production quantity (EPQ) and delivery quantity model for a production system is investigated in this paper. More specifically, an EPQ policy is implemented in the production system, while a smaller shipping quantity is periodically dispatched to the customer. The production system is also responsible for the shipment cost, i.e. a delivery price-based procurement from the customer. The considered cost includes setup cost to launch the batch production, inventory carrying cost, and transportation cost, where the transportation cost is a function of the delivery quantity. A per unit time cost model is developed and analysed to determine the optimal production and delivery quantities. Under some mild conditions, it can be shown that the joint cost function is convex with respect to the production quantity; and the number of delivery is an integer in each replenishment cycle. Computational study has demonstrated the significant impact of the joint decision model on the operating cost. In particular, the reduction in total cost can be more than 15% when inventory carrying costs, and/or transportation costs, are high.     

Inventory and lead time planning with lead-time-sensitive demand

Supply and order lead times can have substantial effects on operations performance and perceived customer service, particularly under uncertain customer demand. Certain customers place a high premium on shorter order lead times, while others may be willing to trade a longer lead time for a lower price. This paper studies a problem in which a supplier wishes to determine the best positioning of a product with respect to order lead time and price. We consider a continuous review inventory replenishment system, where the difference between the procurement lead time and promised sales order lead time influences both cycle stock and safety stock costs, and procurement costs may increase as a result of investment in procurement lead time reduction. We provide models and methods for determining the best combination of price and sales lead time for systems with high economies of scale when demand depends on both sales lead time and price. Our results indicate that for a broad range of practical settings, such systems employ a pure make-to-stock policy or a policy that sets sales lead time equal to the procurement lead time at optimality.