Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

Revenue Management in Make-To-Order Manufacturing: Case Study of Capacity Control at ThyssenKrupp VDM

While revenue management (RM) is traditionally considered a tool of service operations, RM shows considerable potential for application in manufacturing operations. The typical challenges in make-to-order manufacturing are fixed manufacturing capacities and a great variety in offered products, going along with pronounced fluctuations in demand and profitability. Since Harris and Pinder in the mid-90s, numerous papers have furthered the understanding of RM theory in this environment. Nevertheless, results to be expected from applying the developed methods to a practical industry setting have yet to be reported. To this end, this paper investigates a possible application of RM at ThyssenKrupp VDM, leading to considerable improvements in several areas.

Methodology to create cost estimation models for engineer-to-order operations

This research addresses the problem of cost estimation for product development in engineer-to-order (ETO) operations. An ETO operation starts the product development process with a product specification and ends with delivery of a rather complicated, highly customized product. ETO operations are practiced in various industries such as engineering tooling, factory plants, industrial boilers, pressure vessels, shipbuilding, bridges and buildings. ETO views each product as a delivery item in an industrial project and needs to make an accurate estimation of its development cost at the bidding and/or planning stage before any design or manufacturing activity starts. ^ Many ETO practitioners rely on an ad hoc approach to cost estimation, with use of past projects as reference, adapting them to the new requirements. This process is often carried out on a case-by-case basis and in a non-procedural fashion, thus limiting its applicability to other industry domains and transferability to other estimators. In addition to being time consuming, this approach usually does not lead to an accurate cost estimate, which varies from 30% to 50%. ^ This research proposes a generic cost modeling methodology for application in ETO operations across various industry domains. Using the proposed methodology, a cost estimator will be able to develop a cost estimation model for use in a chosen ETO industry in a more expeditious, systematic and accurate manner. ^ The development of the proposed methodology was carried out by following the meta-methodology as outlined by Thomann. Deploying the methodology, cost estimation models were created in two industry domains (building construction and the steel milling equipment manufacturing). The models are then applied to real cases; the cost estimates are significantly more accurate than the actual estimates, with mean absolute error rate of 17.3%. ^ This research fills an important need of quick and accurate cost estimation across various ETO industries. It differs from existing approaches to the problem in that a methodology is developed for use to quickly customize a cost estimation model for a chosen application domain. In addition to more accurate estimation, the major contributions are in its transferability to other users and applicability to different ETO operations. ^

The order selection and lot sizing problem in the make-to-order environment

This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

Planning of a make-to-order production process in the printing industry

Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The production equipment used gives rise to various technological constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technological and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matching-based savings heuristic. We report computational results for a set of problem instances devised from real-world data.

Capacity planning methodology for concurrent engineer -to -order operations

This research focuses on developing a capacity planning methodology for the emerging concurrent engineer-to-order (ETO) operations. The primary focus is placed on the capacity planning at sales stage. This study examines the characteristics of capacity planning in a concurrent ETO operation environment, models the problem analytically, and proposes a practical capacity planning methodology for concurrent ETO operations in the industry. A computer program that mimics a concurrent ETO operation environment was written to validate the proposed methodology and test a set of rules that affect the performance of a concurrent ETO operation. ^ This study takes a systems engineering approach to the problem and employs systems engineering concepts and tools for the modeling and analysis of the problem, as well as for developing a practical solution to this problem. This study depicts a concurrent ETO environment in which capacity is planned. The capacity planning problem is modeled into a mixed integer program and then solved for smaller-sized applications to evaluate its validity and solution complexity. The objective is to select the best set of available jobs to maximize the profit, while having sufficient capacity to meet each due date expectation. ^ The nature of capacity planning for concurrent ETO operations is different from other operation modes. The search for an effective solution to this problem has been an emerging research field. This study characterizes the problem of capacity planning and proposes a solution approach to the problem. This mathematical model relates work requirements to capacity over the planning horizon. The methodology is proposed for solving industry-scale problems. Along with the capacity planning methodology, a set of heuristic rules was evaluated for improving concurrent ETO planning. ^

A gestão de estoques em sistemas produtivos Engineering-To-Order e Make-To-Stock: estudo de casos em empresas do setor gráfico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The contribution of modularity to green operations practices

This paper discusses the possible contributions from modularity and industrial condominiums towards enhancing environmental performance in the automotive industry. The research described in this study is underpinned by a review of journal articles and books on the topics of: modularity of production systems; green operations practices, and the automotive industry and sustainability. The methodology is based on theoretical analysis of the contribution of the modular production system characteristics used in the automotive industry for Green Operations Practices (GOP). The following GOPs were considered: green buildings, eco-design, green supply chains, greener manufacturing, and reverse logistics. The results are theoretical in nature; however, due to the small number of studies that investigate the relationship between modularity and sustainability, this work is relevant to increase knowledge in academic circles and among practitioners in order to understand the possible environmental benefits from modular production systems. For instance, based upon our analysis, we could deduce that the existing modular production systems in the automotive industry may contribute in different ways to the implementation of GOPs. In all types of modularity, product simplification through the use of modules can enhance environmental performance and facilitate further activities such as maintenance and repair contributing to a longer life of cars on the road. Moreover, modules will make automobiles easier to disassembly, so increasing the chances of reuse of valuable components and a better final disposal of scrap. Regarding the potential benefits of each type of modularity, it is expected that modular consortia will have a better integration of environmental practices with suppliers and seize on high efficiency during manufacturing and logistics compared with conventional production systems.

The inherent equitable jurisdiction and the plenary power of the Supreme Court of New South Wales to order the winding up of companies

Not all companies in Australia are amenable to a winding up order pursuant to the Corporations Act 2001 (Cth). The Supreme Court of New South Wales has previously dealt with such winding up applications by apparently focusing on the inherent jurisdiction of the court to consider whether the court has jurisdiction to firstly consider the winding up application. This article proposes an original alternative paradigm: the plenary power provided to the court by s 23 of the Supreme Court Act 1970 (NSW) can be utilised to initially attract the jurisdiction of the court and subsequently the inherent jurisdiction specifically utilising the equitable “just and equitable” ground is available to the court to consider and make such a winding up order if appropriate. Variation of such a paradigm may also be available to the court when considering the inherent jurisdiction in relation to corporation matters more generally.

No-Holdback allocation rules for continuous-time assemble-to-order systems

This paper analyzes a class of common-component allocation rules, termed no-holdback (NHB) rules, in continuous-review assemble-to-order (ATO) systems with positive lead times. The inventory of each component is replenished following an independent base-stock policy. In contrast to the usually assumed first-come-first-served (FCFS) component allocation rule in the literature, an NHB rule allocates a component to a product demand only if it will yield immediate fulfillment of that demand. We identify metrics as well as cost and product structures under which NHB rules outperform all other component allocation rules. For systems with certain product structures, we obtain key performance expressions and compare them to those under FCFS. For general product structures, we present performance bounds and approximations. Finally, we discuss the applicability of these results to more general ATO systems. © 2010 INFORMS.

Implementation of global make to inventory strategy at BASF SE

La optimización y armonización son factores clave para tener un buen desempeño en la industria química. BASF ha desarrollado un proyecto llamada acelerador. El objetivo de este proyecto ha sido la armonización y la integración de los procesos de la cadena de suministro a nivel mundial. El proceso básico de manejo de inventarios se quedó fuera del proyecto y debía ser analizado. El departamento de manejo de inventarios en BASF SE ha estado desarrollando su propia estrategia para la definición de procesos globales de manufactura. En este trabajo se presentará un informe de las fases de la formulación de la estrategia y establecer algunas pautas para la fase de implementación que está teniendo lugar en 2012 y 2013.