Production planning system for a combination of make-to-stock and make-to-order products

This paper deals with the problem of designing a production planning system for a combination of make-to-stock (MTS) and make-to-order (MTO) products where the production facility produces both types of products. Important management points in such production systems are to design an efficient production planning system which can shorten the manufacturing time of MTO products as well controlling the unfilled rate of MTS products to the market demand at a low level. A hierarchical production planning model is introduced in order to design the production planning system. The buffer capacity is set as a design variable for determining production capacity at a higher planning level, and the rule for allocating the production capacity to types of products is adopted as a design variable at a lower level. First, we analyse how these two design variables affect the unfilled rate of MTS products and the average manufacturing time of MTO products. Second, we clarify the relationship of the buffer capacity with the manufacturing time of MTO products and with the required buffer inventory level of MTS products which can maintain the unfilled rate of MTS products to the market demand within an acceptable limit. Third, we show an example of the range of design variables which can control the unfilled rate of MTS products and the manufacturing time of MTO products within their acceptable limits, if the individual limits of the performance measure is given to respond to customer orders quickly.     

Hybrid make-to-stock and make-to-order systems: a taxonomic review

Production planning and control (PPC) systems that employ aspects from both make-to-order (MTO) and make-to-stock (MTS) production control are known as hybrid MTS/MTO systems. While both MTO and MTS separately have been studied extensively, their combined use has received less attention. However, the literature on this topic is growing and this paper shows that the review performed in this paper is an important addition to the field. We categorise relevant literature according to a novel taxonomy and show that hybrid MTS/MTO production control can be used in different contexts. In addition, an overview of the modelling techniques and methods used in these papers is provided. Based on the reviewed literature, relevant research questions and directions for future research are identified. Finally, it is shown that hybrid MTS/MTO production control is prevalent in practice by discussing research with industrial applications. The paper contains an overview of research on hybrid MTS/MTO production control to be used as reference for researchers active in the field, and provides managerial insights and directions for future research on this topic.     

Make-to-order, make-to-stock, or delay product differentiation? A common framework for modeling and analysis

Delaying product differentiation is a hybrid strategy that strives to reconcile the dual needs of high variety and quick response time. A common product platform is built to stock in the first stage of production (called the Make-To-Stock (MTS) stage) which is then differentiated into different products after demand is known in the second stage (known as the Make-To-Order (MTO) stage). In this article, we develop models to compute the costs and benefits of delaying differentiation in series production systems when the order lead times are load dependent. The models are then used to gain insights through analytical and numerical comparisons. For example, we observe the following patterns in a large number of numerical experiments. The effect of congestion in the MTS and MTO stages is asymmetric with tighter capacity at the MTO stage having a greater detrimental effect on the desirability of delaying differentiation. If there is flexibility in choosing the point of differentiation, higher loading is observed to favor later differentiation. Also, if the sequence in which work is performed can be affected, then placing workstations that have a tighter capacity in the MTS stage lowers costs.     

A capacity available-to-promise model for drum-buffer-rope systems

The capacity available-to-promise (CATP) concept, which is designed to enhance the available-to-promise (ATP) feature in MRPII for changing production strategy from make-to-stock (MTS) to make-to-order (MTO), was developed recently. In contrast to an ATP, which is the future uncommitted inventory as projected by master production schedule, a CATP provides a detailed and time-phased diagram of unused production capacity. Hence, a CATP can allow marketing personnel to establish realistic order promise dates and concentrate on selling idle capacity in the future, and enable customers to select their preferred future capacity. This study proposes a CATP model for drum-buffer-rope (DBR) systems. The DBR scheduling system is one of finite capacity schedule systems and is currently being implemented by a growing number of manufacturing companies. This CATP model can help DBR users improve the due-date promising and exploitation of bottleneck. This CATP model can also be embedded in current commercial or private DBR scheduling systems so as to enhance their effectiveness.     

The impact of delayed differentiation in make-to-order environments

To cope with the challenges of product proliferation, many firms are shifting their supply chain structures from make-to-stock (MTS) to make-to-order (MTO). An MTO strategy comes at a price however, as customers must wait longer for their configured products. Incorporating delayed differentiation (DD) in an MTO environment offers the potential of reducing the customer's waiting time, since the generic part/component of the products is made available before receiving customer orders. In this paper, we quantify the trade-offs involved in implementing DD in an MTO environment using both customer waiting time and system cost as performance metrics. We show that under common conditions, the introduction of DD results in shorter waiting times and higher cost over a pure MTO strategy. These results are as expected. However, we also derive conditions where DD results not only in shorter customer waiting time but also lower cost, thus dominating a pure MTO strategy. Through a simulation experiment, we test the robustness of our results for the case where the customer arrivals and production times are generally distributed. For firms with the capability of estimating the customer waiting cost, we derive the optimal base-stock level of the generic component to minimise the total cost.     

Combining make to order and make to stock

In inventory control and production planning one is tempted to use one of two strategies: produce all demand to stock or produce all demand to order. The disadvantages are well-known. In the make everything to order case (MTO) the response times may become quite long if the load is high, in the make everything to stock case (MTS) one gets an enormous inventory if the number of different products is large.In this paper we study two simple models which combine MTO and MTS, and investigate the effect of combining MTO and MTS on the production lead times.     

Make-to-order versus make-to-stock in a production–inventory system with general production times

We study the optimality of make-to-order (MTO) versus make-to-stock (MTS) policies for a company producing multiple heterogeneous products at a shared manufacturing facility. Manufacturing times are general i.i.d. random variables, and different products may have different manufacturing-time distributions. Demands for the products are independent Poisson processes with different arrival rates. The costs of managing the production-inventory system are stationary and include inventory holding and backordering costs. Backordering costs may be $ per unit or $ per unit per unit time. We derive optimality conditions for MTO and MTS policies. We also study the impact of several managerial considerations on the MTO versus MTS decision.     

The design of Make-to-Order supply networks under uncertainties using simulation and optimisation

This paper addresses the problem of designing Make-to-Order (MTO) driven supply networks as is faced by producers of industrial goods. A major challenge in MTO network design is to estimate the operational performance of candidate networks. In particular, the stochastic and dynamic nature of order arrivals and fulfilment processes as well as the need to design a network that enables a timely delivery of ordered products complicate the decision-making. In this paper, a solution approach is presented where simulation is used for assessing the operational performance of candidate networks. The proposed simulation model captures multiple sources of uncertainties and incorporates fundamental control policies for reflecting the autonomous decision-making processes of operational planners. A Variable Neighbourhood Search (VNS) method is presented to guide the search for good network designs. Experiments are conducted on a set of multi-stage networks, where complex products are manufactured in MTO fashion and delivered to customers within a promised order lead time. The results show that our approach effectively produces supply networks that are able to cope with challenges arising from a strong customer orientation.     

Computer-aided production management issues in the engineer-to-order production of complex capital goods explored using a simulation approach

This paper describes the exploration of manufacturing planning and control issues in the capital goods industry using a simulation approach. The companies produce products which have deep and complex product structures and are produced in low volume on an engineer- or make-to-order basis (ETO, MTO). The work reported here draws on the results of surveys of companies involved in the manufacture of capital goods which identified their characteristics of ETO and MTO capital goods companies and their strategic issues. The planning and control approaches adopted in the manufacturing facilities and the difficulties experienced in the application of computer-aided production management (CAPM) systems were also examined. The simulation model developed enables complex manufacturing systems to be modelled and was configured to represent a typical ETO/MTO facility using industrial data. A series of full factorial experiments were performed to explore a number of production management problems identified in surveys including capacity planning, assembly planning and scheduling strategies. Conclusions are drawn on the effects on performance and capacity of: applying minimum set-up and processing times for both major and minor activities; using different data update periods and assembly lead times; and adopting various scheduling and despatching approaches. These results are compared with those obtained by other workers who used survey techniques alone, and have implications for the manufacturers of capital goods.     

Multi-stage simultaneous lot-sizing and scheduling for flow line production

This paper addresses the simultaneous lot-sizing and scheduling of several products in multi-stage flow line production systems consisting of heterogeneous parallel production lines per stage. The limited capacity of the production lines may be further reduced by sequence dependent setup times. Deterministic, dynamic demand of standard products has to be met without backlogging with the objective of minimizing sequence dependent setup, holding and production costs as well as costs for external purchase, overtime, and standby. Different mixed-integer programming (MIP) model formulations are proposed and tested using a standard MIP-solver. Furthermore, construction heuristics like LP-and-Fix and Relax-and-Fix are designed and applied. The solution quality and computational performance of these approaches are examined in several test scenarios.     

基于Supply Hub的供应商配送批量协同决策

分别建立了不考虑和考虑供应商之间配送批量匹配性的生产和配送协同决策模型,采用模拟退火算法(SA)对后者进行求解,结合算例,对两种协同决策模型进行了比较分析.结果表明:考虑供应商之间配送批量匹配性后,供应链系统及供应商单位时间的生产和物流成本显著降低,但Supply Hub运营商与制造厂商的物流成本有所上升.     

Multi-site integrated production-distribution planning with trans-shipment: a fuzzy goal programming approach

In multi-site (parallel) manufacturing systems, each selling region (SR) is usually allocated to a specific manufacturing site (MS) in order to minimise the transportation costs, simplify the planning process, etc. However, such manufacturing systems usually encounter great drawbacks in terms of over-achievement or under-achievement of the forecasted demand due to isolation of the MSs. To cope with this drawback, this paper proposes a novel framework for preparing an optimal aggregate production plan by interconnecting the MSs through lateral trans-shipment. In the presence of fluctuating and dynamic demands, we apply some classic strategies including the inventory holding, back-ordering, and additional capacity options (i.e. overtime and changing workforce level) as well as lateral trans-shipment of products among MSs as the feasible strategies undertaken. Maximising the total profit and minimising the manufacturing lead time are considered as two managerial goals. Due to ambiguousness of some critical parameters as well as vagueness of objectives’ target values, a fuzzy goal programming (FGP) approach with imprecise goal hierarchy is developed for modelling the aggregate production-distribution planning (APDP) problem with trans-shipment. The proposed FGP model is then converted to an equivalent crisp one by combining the two recently developed fuzzy programming approaches. An illustrative example inspired by a real case study is provided to show the usefulness and applicability of the proposed model.     

Comparison of order-fulfilment performance in MTO and MTS systems with an inventory cost budget constraint

The make-to-order or make-to-stock decision is an important issue faced by firms in many industries. In the existing literature, optimisation models comparing the cost of making product to stock versus making it to order have been widely developed. Motivated by the problem faced by a machinery company, we examine the issue from a different perspective and formulate service-maximisation models with inventory cost budget constraints. We compare and analyse order-fulfilment performance measures for the two different production control systems. The goal is to identify the key influencing factors and devise a production strategy that maximises service performance subject to resource constraint. We show that the MTO production control system is preferred in the production system with low component values and long component processing times and high value and short lead time in the final assembly stage; while the MTS production control system is applicable to the production system with high component values and short component processing times and little value and long lead time in the final assembly stage.     

An integrated operations-marketing perspective for making decisions about order penetration point in multi-product supply chain: a queuing approach

This study is dedicated to strategic decision-making regarding order penetration point (OPP), which is the boundary between make-to-order (MTO) and make-to-stock (MTS) policies. This paper considers a supply chain in which a manufacturer produces semi-finished items on an MTS basis for a retailer that will customise the items based on MTO policy. This two-echelon supply chain offers different products to a market comprised of homogenous customers who have different preferences and willingness to pay. The retailer wishes to determine the optimal OPP, the optimal semi-finished goods buffer size, and the price of the products with assumption of price sensitive demand function. Moreover, we consider both shared and unshared capacity models in this paper. A matrix geometric method is utilised to evaluate various performance measures for this system, and then, optimal solutions are obtained by enumeration techniques. The suggested queuing approach is based on a new perspective between the operations and marketing functions which captures the interactions between several factors including inventory level, product pricing, OPP, and delivery lead time. Finally, parameter sensitivity analyses are carried out and the effect of demand on the profit function, the effect of prices ratio on completion rates ratio and buffer sizes ratio and the variations of profit function for different prices, completion percents, and buffer sizes are examined.     

Available-to-promise-based flexible order allocation in ATO supply chains

This paper presents a new available-to-promise (ATP) based order allocation model, which is different from traditional order fulfilment systems in that it considers customer priority in an assemble-to-order (ATO) supply chain environment before the order is fulfilled. First, in terms of customer priority, a pre-allocated model is proposed in order to obtain reserving production capacity ATP and reserving components ATP for each customer class. Then, two order fulfilment models are formulated: the batch order fulfilment model for processing all orders during an order reception period and the real-time order fulfilment model for making order fulfilment decisions when an order arrives immediately. In case that the available production capacity and components are not enough, the ATP searching rules are developed along four dimensions (time dimension, customer demand priority level dimension, product dimension and selling area dimension). Finally, the proposed models are illustrated through an electronic product manufacturing case. The results of the case study show that the performance of the proposed order fulfilment system is better than that of the traditional one.     

Hybrid manufacturing/remanufacturing lot-sizing and supplier selection with returns,under carbon emission constraint

This paper addresses a lot-sizing problem in manufacturing/remanufacturing systems. The studied system is a single manufacturing line where both regular manufacturing and returns remanufacturing processes are carried out, with different set-up costs for each process. We consider also a returns collection phase from customers/distributors with deterministic returns quantities at each period of the planning horizon. The environmental aspect is assumed in this study by considering a carbon emission constraint for the manufacturing, remanufacturing and transportation activities. A mixed integer programming model to minimise the management cost and meet the customer’s needs under different manufacturing constraints is proposed. Otherwise, An adaptation of the well-known Silver and Meal (SM) heuristic and two hybrid method approaches (HM1 and HM2) providing approximates solutions are developed. The mixed integer model was tested on Cplex (Software optimizer), and the obtained results were compared with the ones provided by the adapted heuristic SM and the hybrid methods. The numerical analyses show that hybrid methods provide good-quality solutions in a moderate computational time. The proposed model establishes a collegial and an integrated process that sets values, goals, decisions and priorities along the considered supply chain while taking into account the environmental aspect.     

Decentralised capacitated planning with minimal-information sharing in a 2-echelon supply chain

This paper aims at modelling decentralised planning at the tactical level, with minimal-information sharing coordination, in a 2-echelon supply chain with multiple actors at each echelon. Suppliers manage production and storage at the upstream echelon, while retailers manage transportation and storage at the downstream echelon. The main features of the planning process are (1) decentralisation and coordination using contracts and sharing of only order/supply proposals, and (2) iteration on a rolling horizon. Actor planning is modelled as a capacitated lot-sizing problem on a finite horizon, with the focus on quality of service. The objective is to minimise costs, with a high lost sales penalty if demand is not met. Two other decision problems are pointed out and modelled with Mixed Integer Programming: (1) lost sales allocation between the retailers when their demands cannot be satisfied; and (2) allocation of orders between the suppliers. A multi-agent system combines simulation of the planning process and optimisation of the local decision processes. Several strategies, including retailers’ beliefs about suppliers’ production capacity are proposed and experimentally tested, with two patterns of production capacities. The results compare the proposed allocation strategies and highlight the relevance of the proposed framework for the studied planning problem.     

采购与多层生产计划问题的协同优化

针对生产与采购这两项企业的重要活动,建立了一种采购计划和多层生产计划的集成优化模型,将采购计划、批量计划以及作业排序这三层计划问题进行综合决策。为求解该问题,设计了一种遗传算法和网络优化方法相结合的协同优化策略,遗传算法中每一个个体同时包含了批量计划和作业排序,并调用网络优化模型得出订购策略。数值仿真实验显示了提出的方法求解该类集成优化问题的良好性能。通过与独立优化方法进行比较,显示了协同优化策略的优越性。     

Evaluating the impact of operating environments on MRP system nervousness

Material requirements planning (MRP) systems have become a dominant method in production scheduling and inventory control over the last decade. An MRP is a very complicated information system. It needs to be updated frequently in order to reflect unplanned events, such as machine breakdowns, that exist within or outside the production system. However, the resultant frequent disruption of open orders is a major operational problem of MRP systems, which is generally referred to as 'system nervousness'. MRP system nervousness is caused by various operating variables and environmental factors. The purpose of this paper is to evaluate the impact of operating environments, external or internal, on MRP system nervousness. Several studies have addressed the effectiveness of alternative strategies for reducing MRP system nervousness in a number of operating environments. In this study, a factory simulation is used as an experimental vehicle to investigate the impact on M R P system nervousness of various factors, such as the tightness of capacity utilization and the lot-sizing algorithm used. Based on this study, a set of guidelines is presented which allow MRP users to select an appropriate dampening strategy to cope with system nervousness in face of their operating environments.