Dynamic lot sizing problem with continuous-time Markovian production cost

This paper develops a polynomial algorithm for obtaining dynamic economic lot sizes in a single product multiperiod production system with the objective of minimizing total production and inventory costs over T periods. It is assumed that production costs are linear, inventory costs are concave, setup costs are zero and backlogging is not permitted in all periods. Moreover, the unit production cost is a stochastic variable, which is evolved according to a continuous-time Markov process over the planning horizon. The model is formulated as a stochastic dynamic programming (DP) optimization with the state variable being unit production cost. Then, it is solved using the backward dynamic programming approach. To justify the application of the proposed model, two practical cases are presented.     

Production planning of a hybrid manufacturing-remanufacturing system under uncertainty within a closed-loop supply chain

This paper deals with the production planning and control of a single product involving combined manufacturing and remanufacturing operations within a closed-loop reverse logistics network with machines subject to random failures and repairs. While consumers traditionally dispose of products at the end of their life cycle, recovery of the used products may be economically more attractive than disposal, while remanufacturing of the products also pursues sustainable development goals. Three types of inventories are involved in this network. The manufactured and remanufactured items are stored in the first and second inventories. The returned products are collected in the third inventory and then remanufactured or disposed of. The objective of this research is to propose a manufacturing/remanufacturing policy that would minimize the sum of the holding and backlog costs for manufacturing and remanufacturing products. The decision variables are the production rates of the manufacturing and the remanufacturing machines. The optimality conditions are developed using the optimal control theory based on stochastic dynamic programming. A computational algorithm, based on numerical methods, is used for solving the optimal control problem. Finally, a numerical example and a sensitivity analysis are presented to illustrate the usefulness of the proposed approach. The structure of the optimal control policy is discussed depending on the value of costs and parameters and extensions to more complex reverse logistics networks are discussed.     

Model and analysis of integrated production–inventory system: The case of steel production

The study originated from an industrial case study in the field of steel production, but it presents a larger interest, as many other manufacturing fields have similar concerns (e.g. foundries, food, textile and paper industries). A significant phase of steel manufacturing is the product cooling (likewise, drying in paper and textile production, or maturing in food production). This phase may be completed in different ways, but (1) it must be carried out in the finished product warehouse and (2) it must meet both production optimisation and customer needs. The latter requirement acquires a strategic relevance in JIT environments. The present study proposes a mathematical model to find the optimal production schedule of steel billets, based on the relevant parameters of the productive system (set-up and processing times, demand profile). In the industrial case examined, the negative impact of holding costs on cash flows is also linked to the space required by the cooling process, which depends on the production schedule adopted. In other words, the finished product storage can be considered a part of the manufacturing cycle and impacts on it. In the case of steel plants operating in JIT environments, the warehouse must be promptly emptied and carefully managed to exploit the available space. Thus, the effect of inventory costs is examined in a production–inventory system with finite capacity, where products are made to order and share the same manufacturing facility. The study is completed by an experimental analysis to investigate the effect of variations in the relevant parameters of the problem.     

Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems

This paper presents a method to find the optimal production, repair/replacement and preventive maintenance policies for a degraded manufacturing system. The system is subject to random machine failures and repairs. The status of the system is deemed to degrade with repair activities. When a failure occurs, the machine is either repaired or replaced, and a replacement action renews the machine, while a repair action brings it to a degraded operational state, with the next repair time increasing as the number of repairs increases as well. A preventive maintenance action is considered in order to improve the reliability of the machine, thereby reducing the amount of disruptions caused by machine failures. The decision variables are the production rate, the preventive maintenance rate and the repair/replacement switching policy upon machine failure. The objective of the study is to find the decision variables that minimize the overall cost, including repair, replacement, preventive maintenance, inventory holding and backlog costs over an infinite planning horizon. The proposed model is based on a semi-Markov decision process, and the stochastic dynamic programming method is used to obtain the optimality conditions. A numerical example is given to illustrate the proposed model, and a sensitivity analysis is considered in order to confirm the structure of the control policy and to illustrate the usefulness of the proposed approach.     

The trade-off between production and transportation costs in determining optimal plant size

An important element of manufacturing strategy is to decide on the shipping radius and the size of a geographically focused plant. This decision involves a trade-off between exploiting economies of scale in production by building a large plant and decreasing transportation costs by building a small plant. The paper presents a model for analysing this trade-off. It is shown that scale economies in transportation facilitate the exploitation of production economies of scale. For an optimal sized plant, the ratio of transportation to production costs does not depend on the absolute cost levels in production and transportation, but only the economies of scale present in production and in transportation.     

The evolution of a cellular manufacturing system – a longitudinal case study

This paper describes the evolution of a cellular manufacturing system in a medium-sized company over a 13-year period. The objective of this paper is to analyze the arguments that gave rise to the nearly continuous readjustment of the design of the cellular manufacturing system of this company and the direction in which these adjustments took place. The study indicates that two interrelated factors played an important role in the decision to change the system: the market and manufacturing technology. Analysis of these factors offers important insights into the aspects that need to be taken into account in cell formation. It is argued that a cellular system should reflect market characteristics. New technology, furthermore, demands specialized cells, producing in a multi-shift situation. These two developments point in the direction of market-oriented, reasonably sized, functionally organized manufacturing units. It is argued that market developments, new manufacturing technology and modern production control systems will probably constrain the application area of cellular manufacturing.     

VRP revisited: The impact of behavioural costs in balancing standardisation and variety

The objective of this paper is to bring a new element to the academic (and industrial) debate concerning the optimum level of variety in component design in mass production companies. Many authors have explored the trade-off between functional and variety costs, and this could be considered as a well-acknowledged management issue, at least from an engineering perspective. Nevertheless, while defining the theoretically optimal level of component variety, there are other elements, more related to operators’ attitude or to operative conditions, which may intervene and prevent effective exploitation of the existing variety. These elements have been given scant attention in literature, while they may play a relevant role in real organisations.In this paper, we will present a case study and an analytic model for these “behavioural costs” in manufacturing environments, so as to show how the theoretically optimal amount of variety changes if one takes into account these aspects. Researchers (and practitioners) might leverage on this contribution in order to rejuvenate the Variety Reduction paradigm, and to increase their awareness in designing and managing mass production manufacturing processes.     

THE ROLE OF SUNK COSTS IN THE DECISION TO INVEST IN R&D*

We present a dynamic empirical model of a firm's R&D decisions that is consistent with the existence of sunk R&D costs, taking into account that these costs may differ between small and large firms, and among different technological regimes. We estimate a multivariate dynamic discrete choice model using firm‐level data of Spanish manufacturing for 1990–2000. Conditional on firm heterogeneity and serially correlated unobservable factors, we find that R&D history matters. This true state dependence allows inferring the existence of sunk R&D costs associated with performing R&D. Sunk R&D costs are found to be higher for large, high‐tech firms.     

引入空间维度的经济学分析——新古典经济学理论批判

以新古典经济学为核心的现代主流经济学假设了一个没有空间的世界。克鲁格曼认识到考虑空间维度的重要性,他构造出一个描述收益递增、运输成本和需求相互作用机制的模型,用于解释制造业的集聚现象。在引入空间维度的经济学世界,运输成本是克服空间障碍所花费的成本,运输成本必然要进入描述人们经济行为的需求函数和供给函数。经济过程是规模经济、运输成本、产业间分工和市场范围相互作用的动态过程。需求和供给仅仅是该动态过程的一个侧面,与其说存在静态均衡,不如说存在变化的趋势或方向。引入空间维度的经济学更接近现实的经济,可以解决不考虑空间维度所导致的新古典经济学的理论困境,可以更深入地说明专业化分工和贸易现象,可以更深入地解释交通运输与经济发展的关系。     

Lockout/tagout and operational risks in the production control of manufacturing systems with passive redundancy

This paper addresses problems associated with production control and occupational safety in a manufacturing system prone to failure involving two machines working in passive redundancy. Machines turning out one part experience two modes of failure and repair: firstly, where failure occurs when a machine remains in fair condition; and, secondly, where such failure results in outright breakdown. Accordingly, we examine both modes of failure for their impact on a flexible manufacturing system (FMS) with respect to production control in terms of costs associated with lockout/tagout procedures and corrective maintenance. This study seeks to identify optimal costs related to backlogs, inventories and maintenance over an infinite planning horizon, along with levels of occupational risk where production control includes efficient planning of lockouts/tagouts. Our study offers numerical methods which may be employed to achieve optimal conditions in setting control policies. A numerical example and sensitivity analysis support this approach.     

基于云制造的个性化定制生产模式研究

针对单个企业实施个性化定制生产面临资源不足、能力不强等实际情况，本文结合个性化定制特点及云制造理论提出一种新的个性化定制生产模式。分析了该模式的组织形式，并以云制造平台为核心从内外两个角度研究了该模式的运作方式，最后对其关键技术及优势进行了说明。研究结果表明，基于云制造的个性化定制生产模式不仅能够有效解决单个企业存在的能力不足问题，而且对于提高定制企业应对市场变化的能力也具重要的作用。     

A hierarchical planning system for energy intensive production environments

This paper describes a hierarchical production planning approach with decision support features for energy intensive industries with particular reference to a tile manufacturing factory. In the tiling industry, the facilities which contribute most to the consumption of energy (and, hence, to the production costs) are usually the kilns where the curing operation is carried out. Frequently, the kilns are also the bottleneck in terms of capacity utilization. Thus, in order to save on energy costs, a planning approach which aims at minimizing the number of active kilns throughout the year is needed besides optimizing the process design in the curing department. To achieve the latter goal, it is necessary to take into account demand fluctuations as well as detailed capacity restrictions while deciding on the lot sizes of the products and the kilns on which the products are loaded. Rather than adopting a monolithic mathematical model for developing a desirable production plan, a hierarchical approach which decomposes the problem into two sub-problems is preferred. In the first level, products and capacity are aggregated over the planning horizon to achieve an overall consideration of demand fluctuations over time. Then, the solution provided by the aggregate solution for the current planning period is disaggregated into a detailed lot sizing and loading solution. The disaggregated problem is difficult to solve and hence, a heuristic is proposed here. This planning approach is sustained by a Decision Support System which enables the elimination of possible inconsistencies in the production plan by providing an effective interaction with the decision maker.     

Competition under capacitated dynamic lot-sizing with capacity acquisition

Lot-sizing and capacity planning are important supply chain decisions, and competition and cooperation affect the performance of these decisions. In this paper, we look into the dynamic lot-sizing and resource competition problem of an industry consisting of multiple firms. A capacity competition model combining the complexity of time-varying demand with cost functions and economies of scale arising from dynamic lot-sizing costs is developed. Each firm can replenish inventory at the beginning of each period in a finite planning horizon. Fixed as well as variable production costs incur for each production setup, along with inventory carrying costs. The individual production lots of each firm are limited by a constant capacity restriction, which is purchased up front for the planning horizon. The capacity can be purchased from a spot market, and the capacity acquisition cost fluctuates with the total capacity demand of all the competing firms. We solve the competition model and establish the existence of a capacity equilibrium over the firms and the associated optimal dynamic lot-sizing plan for each firm under mild conditions.     

An extended production/recycling model with stationary demand and return rates

A production–recycling system is investigated. A constant demand can be satisfied with production and recycling. The used items are bought back and then recycled. The non-recycled products are disposed of. Two types of models will be analyzed. The first model examines the EOQ-related costs and minimizes the relevant costs. The second model generalizes the first model with the introduction of the cost function with linear waste disposal, recycling, production and buyback costs. It is asked whether the pure (either production or recycling) or mixed strategies are optimal and it will be shown that under these circumstances the mixed strategies are dominated by the pure strategies. The paper generalizes a former model proposed by the authors for the case of one recycling and one production batch to the case of arbitrary batch numbers.     

Does ICT create a new driving force for manufacturing?—Evidence from Chinese manufacturing firms

The Internet has changed the global economic landscape. In particular, the fast-changing Information and Communication Technology (ICT) has directly led to a far-reaching impact on the production and operation of firms. Many previous studies have discussed the relationship of ICT and the total factor productivity (TFP) of firms, but failed to reach a consistent conclusion. This paper, based on the data of Chinese listed manufacturing firms from 2010 to 2019, explores the impact of ICT on manufacturing firms' TFP and its mechanism, and concludes that ICT have positive correlation with the TFP of manufacturing firms. According to the estimated results of this paper, TFP will increase by about 1.8 % for every 1 % of additional ICT investment. Through channel analysis, this paper finds that the positive effect can be achieved through the following four channels: cutting information search costs, enhancing information processing capabilities, reducing internal capital misallocation, and promoting R&D efficiency. This paper is a supplement to research on firm TFP, provides new micro-evidence for exploring the relationship between ICT and TFP of manufacturing firms, and brings important implications for understanding the role of ICT in firm production activities.     

Short-term decision support system for maintenance task prioritization

Maintenance operations have a direct influence on production performance in manufacturing systems. Short-term production analysis is imperative to enable manufacturing operations to optimally respond to dynamic changes in the system behavior. However, most of the conventional decision support systems for production and maintenance focus on long-term statistic analysis, which is usually not applicable to a short-term period. Maintenance task prioritization is crucial and important for short-term analysis to reduce unnecessary or improper maintenance activities, especially when availability of maintenance resources is limited. The existing methods for maintenance priority assignment are often through heuristic methods or experience, which could cause unscheduled downtime and production losses. In this paper, a short-term decision support system for maintenance task prioritization based on the system operating conditions is introduced. The impact factor for priority assignment is obtained theoretically. A case study based on the simulation of an automotive assembly line illustrates that the proposed short-term system improves the system performance with a lower cost than the long-term method.     

Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach

This paper proposes a two-stage multiple criteria dynamic programming approach for two of the most critical tasks in supply chain management, namely, supplier selection and order allocation. In the first stage, to address multiple decision criteria in supplier ranking, the analytic hierarchy process (AHP) is employed. In the second stage, supplier ranks are fed into an order allocation model that aims at maximizing a utility function for the firm as well as minimizing the total supply chain costs, subject to constraints on demand, capacity, and inventory levels. A dynamic programming approach is crafted to solve the proposed bi-objective model.     

Integrated production planning with sequence-dependent family setup times

This paper proposes an integrated optimization model of aggregate production planning (APP), family disaggregation planning, and family scheduling problems in hierarchical production planning (HPP) systems considering sequence-dependent family setup times. The model obtains the optimal production plan for each product type and product family in each period, together with the globally optimal production sequence of product families in all planning periods. The proposed model is tested with randomly generated experimental data consistent with what is prevalent in the manufacturing industry and its results are compared with those of the traditional HPP models. Our results show that the integrated model realizes greater cost savings.     

Inventory control in a two-echelon dual-channel supply chain with setup of production and delivery

This paper considers a two-echelon dual-channel supply chain model with setup of production and delivery and develops a new inventory control policy for the supply chain. Previously, a two-echelon supply chain model without setup of production and delivery is considered and a one-for-one inventory control policy is applied to the supply chain. In the inventory control policy, production is stopped when the warehouse inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. Moreover, delivery to the retailer is stopped when the store inventory reaches the upper limit and is started again immediately after the inventory drops below the limit. The total cost that consists of inventory holding costs and lost sales cost is considered, and setup costs are not considered in the total cost. Once setup costs are introduced, the one-for-one inventory control policy is no longer appropriate. Then, this paper develops a new control policy for the two-echelon dual-channel supply chain with setup of production and delivery. As performance measure, the total cost that consists of inventory holding costs, lost sales cost, and production and delivery setup costs is considered, and the total cost calculated on the basis of Markov analysis demonstrates the effectiveness of the proposed control policy.     

Efficient location of industrial activity cells in a global supply chain

Inefficient locations for production, distribution and reverse logistics plants will result in excess costs no matter how well material requirements planning (MRP), inventory control, distribution and information sharing decisions are optimized. In this paper we study ways in which aspect of activity cell location decisions can be analyzed within an extended MRP model. This model has previously been extended by including distribution and reverse logistics components in a compact form, presented in Grubbström et al. (2007). Our aim is to demonstrate the basic differences between an approach to location problems with MRP “under the same roof” as the global supply chain, in which transportation time delays and direct transportation costs have substantial influence. We discuss possibilities of how to present location aspects in the supply chain model obtained from combining input–output analysis and Laplace transforms in four sub-systems, namely manufacturing, distribution, consumption and reverse logistics, and show how the transportation costs and lead time influenced by the location of all these activities affect the resulting net present value (NPV). Our aim is to build a model supporting decisions concerning the structure of a supply chain as an alternative to a mixed integer programming formulation. The model developed is based on the use of continuous functions describing spatial distributions of cost and customer demand. Continuous functions are embedded in the MRP extension previously introduced in Grubbström et al. (2007).Location decisions influence (i) production costs, because timing influences the cost of activities involved in creating a product, cf. (Grubbström and Bogataj, submitted for publication), and (ii) logistics costs, which refer to the procurement and physical transmission of materials through the supply chain. In this current paper we wish to combine both of these aspects into a comprehensive model, where we show the interaction between the “space of flows” and the “space of places” as Giovanni Arrighi distinguishes one from the other in his book The Long Twentieth Century.