Multi-level Product Structure Research Articles

Dynamic lot-sizing for remanufacturing systems with multi-level structured products and components commonality

This study addresses dynamic lot-sizing for remanufacturing systems in which end-of-use/life products are disassembled into their components on a disassembly workstation, each recoverable part is reprocessed on one of parallel reprocessing workstations and the reprocessed and newly purchased ones, if required, are reassembled into remanufactured products on a reassembly workstation. The problem is to determine disassembly, reprocessing, reassembly lot-sizes as well as the reprocessing workstation to reprocess each recoverable part while satisfying dynamic remanufactured product demands and workstation capacities in each period of a planning horizon. As an extension of the previous studies, multi-level structured products with components commonality are considered for the objective of minimizing the sum of setup, operation and inventory costs. A mixed integer programming model is developed, and due to the problem complexity, two types of heuristics are proposed that obtain an initial solution using a greedy-type heuristic and improve it by two types of bi-directional moves with various priority rules for forward and backward moves, i.e. individual-moves and cluster-moves. Computational results show that the cluster-move based approach that considers components commonality explicitly outperforms the individual-move based one significantly and gave fast near optimal solutions for small sized test instances. Finally, a sensitivity analysis on different multi-level product structures were done and the results are reported.

Limited Search Space-Based Algorithm for Dual Resource Constrained Scheduling Problem with Multilevel Product Structure

This study addresses the dual resource constrained flexible job shop scheduling problem (DRCFJSP) with a multilevel product structure. The DRCFJSP is a strong NP-hard problem, and an efficient algorithm is essential for DRCFJSP. In this study, we propose an algorithm for the DRCFJSP with a multilevel product structure to minimize the lateness, makespan, and deviation of the workload with preemptive priorities. To efficiently solve the problem within a limited time, the search space is limited based on the possible start and end time, and focus is placed on the intensification rather than diversification, which can help the algorithm spend more time to find an optimal solution in a reasonable solution space. The performance of the proposed algorithm is compared with those of a genetic algorithm and a hybrid genetic algorithm with variable neighborhood search. The numerical experiments demonstrate that the strategy limiting the search space is effective for large and complex problems.

An artificial bee colony algorithm for a two-stage hybrid flowshop scheduling problem with multilevel product structures and requirement operations

Real world final products have almost multilevel structures, where different items are assembled together according to predefined bill of materials. Also, each item must experience a set of processes before assembly according to a given precedence relation between the processes. This paper considers a hybrid flowshop with two stages for processing on items and assembling final products. The first stage is dedicated to processing on items and consists of some non-identical parallel machines. After finishing processing on the items on the first stage, assembly of items into final products starts at the second stage. The production manager desires to minimise the maximum completion time (i.e. makespan). Then, the problem is modelled as an integer linear program and is solved by Lingo. As the problem is NP-hard, an artificial bee colony algorithm along with a genetic algorithm is developed to obtain near-optimal solutions in reasonable run-times. Further, efficiency of the solution methods is examined on different problem instances.

Multi-period lot sizing and job shop scheduling with compressible process times for multilevel product structures

This paper presents mathematical modelling of joint lot sizing and scheduling problem in job shop environment under a set of working conditions. The main feature of the problem is to deal with flexible machines able to change their working speeds, known as process compressibility. Furthermore, produced items should be assembled together to make final products. In other words, the products have a multilevel structure, shown with bill of materials. As the problem is proved to be strongly NP-hard, it is solved by a memetic algorithm here. Computational experiences on the data of ‘Mega Motor’ company are reported. Also, further experiences on random test data confirm the performance of the proposed method with less than 5.02% optimality gap while solving the problems in very shorter times than CPLEX 12.0.

Capacitated lot-sizing with extensions: a review

The capacitated lot-sizing problem (CLSP) is a standard formulation for big bucket lot-sizing problems with a discrete period segmentation and deterministic demands. We present a literature review on problems that incorporate one of the following extensions in the CLSP: back-orders, setup carry-over, sequencing, and parallel machines. We illustrate model formulations for each of the extensions and also mention the inclusion of setup times, multi-level product structures and overtime in a study. For practitioners, this overview allows to check the availability of successful solution procedures for a specific problem. For scientists, it identifies areas that are open for future research.

A genetic algorithm for multi-level, multi-machine lot sizing and scheduling

This contribution introduces a mixed-integer programming formulation for the multi-level, multi-machine proportional lot sizing and scheduling problem. It also presents a genetic algorithm to solve that problem. The efficiency of that algorithm is due to an encoding of solutions which uses a two-dimensional matrix representation with non-binary entries rather than a simple bitstring. A computational study reveals that the proposed procedure works amazingly fast and competes with a tabu search approach that has recently been published. Scope and purpose The logic of Manufacturing Resource Planning (MRP II) is implemented in most production planning software packages. In the short-term scope, where lot sizing and scheduling has to be done, MRP II systems basically pass three phases: First, lot sizes are computed while disregarding capacity constraints. Multi-level product structures are taken into account in a level-by-level manner starting with end items. Second, lot sizes are adapted to meet capacity restrictions. This time, precedence relations among items are not taken into account. Finally, sequence decisions are made. Following this strategy is reported to result in high work-in-process and long lead times. To cure these shortcomings, an approach for simultaneous lot sizing and scheduling is required where multi-level product structures and several scarce capacities are taken into account. Unfortunately, such methods have not been presented yet. To close this gap is our aim.

A net present value approach to safety stocks in a multi-level MRP system

The Laplace transform and input–output Analysis have been used for formulating a basic theory for material requirements planning (MRP) in a sequence of recent papers. The transform has been used for describing time developments and lags of the relevant production, demand and inventory variables in a compact way including effects of order flows and lead times. Secondly, the transform has functioned as a generating function, and thirdly, the transform has been applied for assessing cash flows adopting the net present value (NPV) principle (or the annuity stream which is a variation of NPV). Input-output Analysis, in particular, the input matrix, has been applied for describing multi-level product structures. This has made the analysis compact and distinct. In the current paper the analysis of determining optimal safety stock levels in MRP systems is extended from a single-level model recently investigated to a multi-level system assuming production to take place according to a lot-for-lot (L4L) policy when applying the NPV as the objective criterion and disregarding the opportunities for joint set-ups. Relaxing the L4L assumption is also discussed.

Multi-level lotsizing and scheduling by batch sequencing

We consider a single-machine scheduling problem with a multi-level product structure. Setups are required if the machine changes production from one product type to another, and the scheduling decision must satisfy dynamic demand. We propose a lotsizing as well as a scheduling model, and we compare solution procedures for both models on a very restricted set of instances. As a result the multi-level structure complicates the inventory balance constraints in the lotsizing model. In the scheduling model, however, the multi-level structure translates into precedence constraints between jobs (leading to a smaller search space) which allows it to solve the scheduling model to optimality.

A net present value approach to safety stocks in planned production

In a number of recent papers, the Laplace transform together with input-output analysis has been applied for the sake of formulating a basic theoretical description of material requirements planning (MRP). The transform approach has had a threefold use; on the one hand, it has been useful for describing time developments of the relevant production, demand and inventory properties in a compact way including effects of order flows and lead times. Second, the transform also captures stochastic properties by functioning as a generating function, and, third, the transform is easily applied for assessing the resulting cash flows when adopting the net present value (NPV) principle (or the annuity stream principle which is a variation of NPV). Input-output analysis, in particular the input matrix, is applied for describing multi-level product structures, which has made the analysis concise and distinct. In this paper we extend the analysis of determining optimal safety stock levels for a sequence of planned production decisions (a one-level MRP system) by applying the annuity stream as a criterion to a simple model instead of the average cost approach previously used.

Progressive engineering changes in multi-level product structures

One of the objectives of engineering changes is to redesign product/component parts to perform better or to be produced more efficiently. Frequent engineering changes, however, contribute to scheduling instability in multi-level product structures in addition to obsolete inventories. In this paper, we consider progressive probabilities of engineering changes as opposed to the constant probabilities generally assumed in most related studies. Realistically, the probability of changing a part at a certain level is affected by the changes in its parent levels. Thus, the likelihood of changes may progressively cascade from the top to the bottom of the product structure. An analytical procedure is developed to compute progressive probabilities of engineering changes. Then, a sensitivity analysis is performed to see how the shape of product structure and component commonality affect resultant progressive engineering changes for the lower-level items in the product structure. We find that engineering changes of a component part are affected significantly by the number of immediate parent items and their magnitudes of engineering changes. However, the depth of product structure has no significant impact on the engineering change of any item.

The effects of purchased parts commonality on manufacturing lead time

Manufacturing managers as well as researchers suggest that reducing manufacturing lead time is essential for competing in world‐class manufacturing environments. To achieve world‐class manufacturing status, organizations implement a variety of programmes to decrease manufacturing lead time. Uses simulation to analyse the effect of purchased parts standardization on manufacturing lead time under the assumption of limited vendor delivery uncertainty. Creates a wide range of degrees of commonality based on three sets of multilevel product structures with the variations of end‐item demand and quantity usage. The statistical results indicate that: increased commonality lowers manufacturing lead time; a more informative commonality measure other than the well‐known degree of commonality index (DCI) is necessary to represent the actual commonality; and the distribution of purchased parts usage across different end items affects manufacturing lead time performance. The results provide important implications for both manufacturing and product design management.

Simulated annealing and genetic algorithms for scheduling products with multi-level product structure

We consider a short-term production scheduling problem in a manufacturing system producing products with multi-level product structure, and their components and subassemblies. The problem is to schedule production of components, subassemblies, and final products with the objective of minimizing the weighted sum of tardiness and earliness of the items. We consider due dates of final products, precedence relationships among items, and processing capacity of the manufacturing system. The scheduling problem is solved with simulated annealing and genetic algorithms, which are search heuristics often used for global optimization in a complex search space. To compare the performance of these algorithms with the finite loading method, which is often used in practice, computational experiments are carried out using randomly generated test problems and results are reported.

Combined demand and lead time uncertainty with back-ordering in a multi-level product structure environment

Abstract The performance of two lot-sizing algorithms incorporating back-orders is evaluated and compared with several traditional lot-sizing rules. This comparison is undertaken for a multi-level product structure environment operating under a rolling horizon in the presence of both demand and lead time uncertainties. By means of simulation and statistical analysis of the simulation output, the impact on system performance of a variety of demand and lead time scenarios, product structures, cost parameters and lot-sizing, is evaluated. The conclusions drawn emphasize important differences in the influence of the factors on system performance given the presence or absence of uncertainty.

MRP systems under supply and process uncertainty in an integrated shop floor control environment

Abstract We investigated the effect of supplier and process uncertainty in a real time MRP environment. The environment modelled is supported by an ‘on line’ data monitoring and data collection system such that the activities of the shop floor and the receiving area are incorporated within the MRP database as they occur. The purpose of the model is to evaluate the operation of an integrated shop floor control/M R P system in a multi-level product structure environment which operates on a rolling horizon basis. The interaction of supply/process uncertainty with product structure and choice of lot sizing rule is examined for various cost factors. The presence of uncertainty is found to greatly complicate the operation of the MRP system. In addition, supply/process uncertainty combines with product structure and the choice of lot sizing rule, to impact the cost performance of the system. The significance of these interactions was confirmed by the formulation and testing of several hypotheses. Based on these ...

Lead time uncertainty with back-ordering in multi-level product structures

The performance of lot sizing algorithms incorporating back-orders is evaluated and compared with several of the traditional lot sizing rules. This comparison is undertaken for a multi-level product structure environment operating under a rolling horizon in the presence of lead time uncertainty. By means of simulation, the impact of a variety of lead time scenarios, product structures and cost parameters on lot sizing is examined. It is shown that unlike in the deterministic environment, the back-ordering algorithms can yield superior performance in an uncertain environment.

The performance of materials management in multi-level product structures with demand uncertainty and back-ordering

This paper investigates the impact of planned backordering in the context of demand uncertainty for a multi-level product structure environment operating under a rolling horizon. To this end, the performance of lot sizing algorithms incorporating back-orders is evaluated for such an environment by means of simulation modeling. Given the presence of demand uncertainty, the results suggest that backordering algorithms can sometimes improve performance.