Make-to-stock Research Articles

Implementing workload control through lean-based project in MTO-MTS environment

Purpose Due to high customization, companies, which used to follow the make-to-stock (MTS) strategy, are now adopting the make-to-order (MTO) strategy along with MTS in order to cope with high variability in customer demand. Although lean is quite popular in general, its advantage in MTO-MTS environment is quite rare. Therefore, the purpose of this paper is to show the benefits of lean techniques in this environment.Design/methodology/approach A popular furniture company in Italy is selected for the longitudinal action research and as a part of the lean project, workload control (WLC) is deployed in the selected company. Data were collected through on-site interviews, potential areas of improvement were identified and then suitable countermeasures were proposed and adopted.Findings This study reveals that the implementation of lean techniques including WLC in a furniture company reduces the throughput time and improves the inventory turnover.Research limitations/implications This research is based on a single company. Additional empirical studies can help to refine our proposition.Practical implications The paper shows the practical implementation of WLC as a part of the lean project in MTO-MTS environment. It provides the practitioners and consultants with the way of implementing lean techniques in companies that are planning to adopt MTO-MTS hybrid strategy.Originality/value This is the first paper that aims to assess the efficiency of the adaption of WLC based on lean principles in a company using MTO-MTS hybrid strategy. Hence, the results are highly valuable for similar companies, especially when are facing transition situations (e.g. from MTS to MTO-MTS).

Merging make-to-stock/make-to-order decisions into sales and operations planning: A multi-objective approach

With the advent of mass customization and product proliferation, the appearance of hybrid Make-to-Stock(MTS)/Make-to-Order(MTO) policies arise as a strategy to cope with high product variety maintaining satisfactory lead times. In companies operating under this reality, Sales and Operations Planning (S&OP) practices must be adapted accordingly during the coordinated planning of procurement, production, logistics, and sales activities. This paper proposes a novel S&OP decision-making framework for a flow shop/batch company that produces standard products under an MTS strategy and customized products under an MTO strategy. First, a multi-objective mixed-integer programming model is formulated to characterize the problem. Then, a matrix containing the different strategies a firm in this context may adopt is proposed. This rationale provides a business-oriented approach towards the analysis of different plans and helps to frame the different Pareto-optimal solutions given the priority on MTS or MTO segments and the management positioning regarding cost minimization or service level orientation. The research is based on a real case faced by an electric cable manufacturer. The computational experiments demonstrate the applicability of the proposed methodology. Our approach brings a practical, supply chain-oriented, and mid-term perspective on the study of operations planning policies in MTS/MTO contexts.

Evaluation of postponement strategy in the production of table wine in Brazil: a discrete event simulation approach

PurposeThe purpose of this paper is to develop an approach to evaluate the partial postponement strategy and compare it with postponement and make-to-stock (MTS) strategies in the production of table wine in wineries in the state of Minas Gerais (south-eastern Brazil).Design/methodology/approachAn approach based on discrete event simulation was developed to support decision-making in the wine sector. Simulation models were used to analyse partial postponement, postponement and MTS strategies in wine production. These models were inspired by a typical table wine producer selected from an exploratory study conducted in 12 wineries of Minas Gerais state in Brazil.FindingsHybrid strategies, such as partial postponement, favour the advantages of postponement and MTS depending on the portion of semi-finished and finished goods adopted. Wine production characteristics favour postponement and partial postponement with high semi-finished product levels (customer order-driven product) because this allows companies to reduce their inventory of bottles, despite possible increases in lost sales and costs. MTS and partial postponement with high finished product levels (forecast-driven product) present higher costs with bottled wine storage; however, these strategies reduce lost sales and improve agility and reliability in deliveries.Research limitations/implicationsFuture research should analyse the production of table wines in other regions of the country and the production of fine wines.Practical implicationsThe findings suggest promising perspectives for real-life applications in wineries in Brazil and other countries.Originality/valueSimulation techniques allow the analysis of production strategies in little-known industries, such as table wine production in Brazil. The approach developed is flexible enough to support decisions and to be adapted to companies’ and markets’ characteristics and to test specific strategies.

Flow shop optimization of hybrid make-to-order and make-to-stock in precast concrete component production

As the world environment is faced with the severe challenge of global warming, prefabricated construction is the path for the construction industry towards green production. Precast component manufacturers produce standardized and non-standardized components simultaneously. Non-standard components are produced make-to-order (MTO). Standard components are produced make-to-stock (MTS). In this study, the flow shop precast component production scheduling problem under a hybrid MTO-MTS environment is studied. A hybrid MTO-MTS precast component flow shop production model is developed. The object is to minimize total tardiness and earliness of delivery. An iterative job insertion algorithm based on whale optimization is developed. The proposed method involves two stages: scheduling and insertion. The first is to optimize the scheduling of customized MTO components. Then the standard MTS job is inserted. Through the computational evaluation, the performance and effect of the proposed approach are tested. It can conclude that the proposed algorithm contributes to the effective and efficient optimization of Hybrid MTO-MTS precast component production.

Model comparison and management optimization of pump production organization

This manuscript aims to explore the impact of production organization mode on the inventory and delivery rate of pump enterprises and optimize the production management of pump enterprises. The system dynamic model and simulation test method were used to compare the changes in the inventory, productivity and delivery rate of pump enterprise under the traditional make-to-order (MTO) and make-to-stock (MTS) organizational modes. Following the above analysis, the optimized pump order production management mode combined with MTO & MTS was put forward, and the fuzzy comprehensive evaluation method was used to evaluate the three above modes. When customer demand scarcely fluctuates and is easily predictable, the MTO production organization mode can be adopted; when customer demand fluctuates sharply and is difficultly predicted, the MTO & MTS combined mode should be selected. According to the results of the fuzzy comprehensive evaluation, the MTO & MTS mode is the best choice for pump enterprises. Considering that the pump demand is sensitive to the season and natural environment, the optimized mode is suitable for the production and inventory management of pump enterprise.

Analysis of production resources improvement strategies in make-to-stock environments managed by the simplified drum-buffer-rope system

Abstract: Theory of Constraints (TOC) states that every system has a single constraint that limits its performance, on which improvement efforts should be concentrated. This paper compared, through computer simulation, several methods of identifying the capacity-constrained resource in the perspective of a process of continuous improvement. Six make-to-stock (MTS) production line configurations managed by the Simplified Drum-Buffer-Rope (S-DBR) system were simulated, in which six improvement methods were applied, three of them based on the TOC literature, and their performance measured and compared in terms of cycle time and order fill rate. The results showed that, in balanced systems, improvements spread over all resources allowed better results, because, in this case, it is necessary to improve everything to benefit the overall performance. In unbalanced environments, on the other hand, the three methods recommended by TOC, which recommend efforts concentrated on the weakest point of the system, achieved superior performance, with emphasis on the strategy based on the level of utilization. In addition to advancing the frontiers of knowledge in continuous improvement and TOC, the research results show that managers should focus their attention on the resource with the highest degree of utilization to get better and faster performance gains.

Performance Analysis of Hybrid MTS/MTO Systems with Stochastic Demand and Production

We present a comprehensive numerical approach with reasonably light complexity in terms of implementation and computation for assessing the performance of hybrid make-to-stock (MTS)/make-to-order (MTO) systems. In such hybrid systems, semi-finished products are produced up front and stored in a decoupling inventory. When an order arrives, the products are completed and possibly customised. We study this system in a stochastic setting: demand and production are modelled by random processes. In particular, our model includes two coupled Markovian queues: one queue represents the decoupling inventory and the other the order backlog. These queues are coupled as order processing can only occur when both queues are non-empty. We rely on matrix analytic techniques to study the performance of the MTO/MTS system under non-restrictive stochastic assumptions. In particular, we allow for arrival correlation and non-exponential setup and MTS and MTO processing times, while the hybrid MTS/MTO system is managed by an (s,S)-type threshold policy that governs switching from MTO to MTS and back. By some numerical examples, we assess the impact of inventory control, irregular order arrivals, setup and order processing times on inventory levels and lead times.

Managing product variety with mixed make-to-stock/make-to-order production strategy and guaranteed delivery time under stochastic demand

Firms often use a facility to produce both Make-to-Stock (MTS) and Make-to-Order (MTO) items. This study provides insights into conditions favoring the adoption of such a mixed MTS-MTO production strategy. Past studies ignore the influence of a one-to-many relation between semi-finished goods and products, and a guaranteed lead-time for MTO products, with uncertain product demand. The problem is modeled as a two-stage stochastic 0–1 integer, non-linear programming problem. In Stage 1, before demand realization, operations determine the product-wise mode of production and inventory level of semi-finished goods/MTS products, and marketing determine the guaranteed lead-time for MTO products. In Stage 2, product demand is realized, and it decreases linearly with lead-time and has a stochastic error component. The demand for MTS products is fulfilled from available inventory, and semi-finished goods are allocated to meet the demand of MTO products and build a stock of MTS products. The objective is to maximize the expected profit per-unit time. Sensitivity analysis of key problem parameters demonstrates that: (1) the integrated-firm can provide smaller lead-times under demand variability, (2) high holding cost of semi-finished goods, high lead-time sensitivity of demand, and high demand variability & low production rate promote mixed strategy over MTO strategy, and (3) high demand variability promotes substitution among semi-finished goods. A Hybrid Greedy and Non-linear Branch & Bound method (featuring problem-specific cuts and search & branching strategy) is proposed to solve real-life problems. This method provides a better solution and a smaller relative gap than commercial solver Simple Branch and Bound.

Determining the changes in the Master Production Schedule (MPS) at the company with Make to Stock (MTS) and Make to Order (MTO) strategies

The master production schedule (MPS) planning is influenced by the manufacturing environment. Therefore, the process of MPS planning with make to stock (MTS) strategy will be different from make to order (MTO) strategy. The MPS is based on production capacity, changes in inventory of finished products, fluctuations in demand, efficiency and utility of production factors, and lot size. Companies with MTS strategies make production schedules based on estimated demand so that customer demand can be met from stock products. While companies with an MTO strategy make a production schedule after the order is received. This paper discusses how the time fence approach is used to change MPS for companies with the MTS and MTO strategies simultaneously. With the time fences approach, companies can determine when orders can be received or rejected by looking at the position of the order on the existing MPS. This paper describes a case of applying the time fences approach to determine the MPS changes in a garment company that produces bed covers sets as the MTS products and other products as MTO products. This paper also explains the procedures to determine changes in the MPS based on predetermined time fences.

A System Dynamics Approach Towards Analysis of Hybrid Make-to-Stock/Make-to-Order Production Systems

Hybrid Make-To-Stock (MTS)/Make-To-Order (MTO) production system benefits from both pure MTS and MTO systems and thus, is regarded as a valuable production system in order to respond today’s market conditions such as demand uncertainty, shortage of raw materials, and high inventory holding costs. Our purpose is to explore such systems over covering most of the influential factors that have not been taken into account so far. Hence, a system dynamics (SD) model is proposed in this study considering three different series of workstations (MTS, MTO, and MTS/MTO) in a manufacturing firm with a continuous production line. The performance of the developed model is assessed in terms of holding costs as well as product’s delivery lead-time. Moreover, this study considers the impacts of some significant, exogenous variables such as different outlays including operating expenses, holding costs, and the company’s net profit. The results show the superiority of our proposed model in contrast with previous studies in a cost-oriented point of view.

Optimal MTS and MTO Hybrid Production System for a Single Product Under the Cap-And-Trade Environment

This paper studies the optimal production planning in a hybrid Make-To-Stock (MTS) and Make-To-Order (MTO) production system for a single product under the cap-and-trade environment. The manufacturer aims to minimize the total cost in production, inventory and emissions allowances trading. The decisions include the selection of production mode (pure MTS, pure MTO or hybrid MTS/MTO), the inventory and emissions trading quantity. We derive the optimal solution analytically. We show that the cost of optimal MTO/MTS hybrid production strategy is remarkably less than that of either pure MTO or pure MTS production strategy alone. Compared with the no initial carbon quota and trading environment, there are significant differences in the optimal production decisions under trading environment. When the emissions cost is a source of costs, the manufacturer has to face more costs pressure even if there is no emissions allowance trading. In particular, the results show that the initial emissions allowance determines the optimal production decision and emissions allowance trading decision in cases where the difference between the inventory cost for per unit product and the delayed delivery cost for per unit order is between the minimum and the maximum emissions cost and has no effect on production mode and emissions allowances trading decision in other cases. These conclusions will provide optimal production decision and carbon trading decision for the manufacture under a cap-and-trade environment.

An advanced order acceptance model for hybrid production strategy

Competitors stand out through commitment to providing excellent customer service. Many organizations strive to promote their order promising system to generate more reliable quotes with quantity and due date constraints. This paper develops a Capable-to-Promise (CTP) based Order Acceptance Model (OAM) for a Hybrid Production Strategy (HPS) based on the positioning of the Customer Order Decoupling Points. The proposed model allocates the uncommitted availability and planned production receipts to current and anticipation of future needs. A Mixed-Integer Linear Programming (MILP) is developed to determine the optimal order quantities based on the resource availability. The proposed model efficiently mitigates the risk of not being reliable in the commitments due to discrepancies between the real and unused quantities. The CTP based OAM is compatible with a HPS with both make-to-order (MTO) and make-to-stock (MTS). The presented model encompasses four steps. First, demands for MTO products are collected in batches on daily basis and a forecasting model is applied to predict orders for MTS products. Secondly, the quantity-based Revenue Management approach is used to prioritize orders. Afterwards, the optimization model assesses the availability of resources in order to produce collected orders. The final step is to accept valuable orders based on the resource availability. In order to illustrate the applications of the modeling approach, two case studies are provided.

A review of the literature on mixed make-to-stock/make-to-order production systems: major findings and directions for future research

Research on production strategies have mainly focused on make-to-stock (MTS), make-to-order (MTO) or hybrid MTS-MTO mode of production. However, firms also manufacture both MTS and MTO items in a single facility. This is popularly known as mixed MTS-MTO production strategy. A content-analysis-based literature review is conducted to identify: 1) the conditions favouring adoption of these systems; 2) the issues in these systems and our current understanding of addressing these issues; 3) the challenges in improving these systems. In addition, we also examine the modelling approaches used to design mixed MTS-MTO systems. The study provide insights to the operations managers to suitably design the production systems in order to derive competitive advantage.

The Shen Model for Make-to-Order SME’s

This paper describes a new model developed for make-to-order (MTO) sectors namely SHEN Principles, which aims to fill a gap in the world-class manufacturing (WCM) literature that concentrates on the characteristics of the larger traditional make-to-stock (MTS) sector. Using evidence from the literature, especially the MTO literature and the more comprehensive WCM models, a new model was devised. This was then modified in the light of case study evidence collected from the six MTO companies ranging from small-to medium-sized MTO companies. The model presented in this paper known as “SHEN Principle”, will be the current version of the model after all the modifications have been incorporated.

An Automated Information System for Medium to Short-Term Manpower Capacity Planning in Make-To-Order Manufacturing

In today’s tough economy, it is important for (Make-To-Order) MTO companies to be responsive to customer demand and market fluctuations and to keep the costs as low as possible at the same time. Unlike in Make-To-Stock (MTS), MTO companies hold capacity in reserve. Thus, they are able to make efficient utilization of available capacity to satisfy customer needs. This then leads to a constant capacity planning problem. The companies are facing fluctuations between overload by lack of sufficient capacity, and idleness by excess of capacity comparing to the level of demand. Among all the planning resources, the available manpower is one of the most essential parts of the MTO operations. Therefore, the allocation and adjustment of manpower capacity that suits different planning horizons is a predominant measure to meet the changing capacity demands. Nonetheless, a signing each individual labor to various types of tasks and orders on a day to day basis continually for the planning horizon of several weeks or months is difficult. This paper presents an approach of automated manpower planning model which can be used by MTO operations to achieve a better transparency and synchronization of capacity load for short to medium planning horizons. The approach is implemented as a software tool to automate the data processing and analysis, which helps to dramatically reduce the corresponding data operation efforts and planning time. This paper also presents the validation of the approach and tool in a real production unit in a German small MTO manufacturing company.

A graph-based decision support system for analyzing hybrid make-to-stock/make-to-order manufacturing environments

Goal: This paper aims to facilitate production-planning strategies for demand responsiveness. Our paper implements graph-rewriting systems towards supporting operative decision making in production environments.
 Design/Methodology/Approach: We design a decision support approach which is able to recognize and resolve conflicts amongst workstations in a hybrid production system. During the proposed stages of the presented approach, we rewrite the hybrid system by means of graph representation procedure, identify conflicts among the workstations by means of the developed graph coloring algorithm, and evaluate performance of the reorganized system by defining key performance indicators for the presented system.
 Results: We prove that the graphs’ chromatic numbers in such systems are less than or equal to entire number of dummy nodes applied to the system by means of our proposed algorithm. Furthermore, the presented structure improves the performance of the system by analyzing production bottlenecks.
 Limitations of the investigations: we only considered the Key Performance Indicators according to products, workstations, and customers. However, the problem can be more generalized by adding some more elements.
 Practical Implications: Our methodology enables managers to assess the performance of the reorganized system after applying the heuristic algorithm, by means of representing a performance evaluation procedure.
 Originality/ Value: We focus on presenting a novel structure to help companies using hybrid make-to-stock (MTS)/make-to-order (MTO) production strategies to (1) identify conflicting workstations and the relations among them, (2) propose dialectical prioritization rules and techniques by means of graph-coloring concepts for resolving the conflicts, (3) reorganize the system, and evaluate performance.

Total productive maintenance of make-to-stock production-inventory systems via artificial-intelligence-based iSMART

ABSTRACT Total Productive Maintenance (TPM) is a critical activity that significantly reduces lead times and uncertainty in Make-To-Stock (MTS) production systems, thereby increasing the efficiency and profit margins of the associated firm. TPM problems can be set up as semi-Markov decision processes (SMDPs) and solved optimally using classical dynamic programming (DP) on small-scale problems. However, on large industrial-scale problems, DP breaks down, and one must then resort to an artificial intelligence (AI) technique called reinforcement learning (RL). This work presents a new AI algorithm for solving SMDPs, called iSMART, an acronym for imaging Semi-Markov Average Reward Technique. iSMART requires a significantly lower modelling and computational effort than classical DP, where estimating the transition probabilities can itself be very time-consuming and mathematically challenging for large-scale problems. Further, unlike previous RL algorithms for SMDPs, iSMART does not need exploration decay. This means iSMART eliminates an additional parameter that requires significant tuning in the traditional RL-based solution approach. Modern AI based in deep learning seeks to reduce dependence on tuning parameters. iSMART is designed in this spirit for solving TPM problems in MTS production systems, where it is shown to deliver optimal solutions on small-scale problems and near-optimal ones on large-scale problems.

Managing supplier flexibility performance as a relational exchange investment in make-to-stock versus make-to-order production environments

PurposeThis paper aims to develop and test a model of buyer–supplier relational investment that links supply chain integration (SCI) to supplier flexibility performance (SFLEX) advantages in different manufacturing environments. Relational stability (RS) and information quality (IQL) are viewed as key indicators of intermediating commitment investments in supplier relationships to help support supplier accommodations for special requests for order flexibility. The model is applied to investigate the relative importance of manufacturer relational investments with suppliers in both make-to-stock (MTS) and make-to-order (MTO) production environments.Design/methodology/approachA survey of 206 US manufacturing firms was used to test the proposed research model using structural equation modeling and multiple-group analysis techniques.FindingsSocial exchange investments in relationship stability and information quality are found to fully mediate the positive performance relationship between supply chain integration and supplier flexibility performance for manufacturers. However, the relative importance of each form of investment in enhancing supplier flexibility performance varies based on the buyer’s (manufacturer’s) order fulfillment environment (make-to-stock versus make-to-order).Originality/valueThe proposed model may assist manufacturers make more informed relational exchange investments and supply chain configuration decisions that most conducive to enhancing supplier flexibility performance for different production environments.

Synchronized scheduling of make to order plant and cross-docking warehouse

To be part of very competitive supply chains, retailers and wholesalers expect small batch deliveries within short and dependable time window. Manufacturing companies have to cater to their customer’s requirement and shift their production strategy from traditional make-to-stock (MTS) to make-to-order (MTO). Meanwhile, the operation in warehouse is also changed from long term storage to short term cross-docking (CD). Based on a real-life industrial case, it can be found that, in order to achieve overall optimization, the production decision and warehouse decision should be considered simultaneously. In this paper, the specific features of synchronized production logistics scheduling in MTO plant and CD warehouse have been studied and the mathematical model of MTO-CD synchronization has been formulated. A meta-heuristic algorithm HGA-OLS has been proposed in this study. According to the computational experiments and algorithm comparison, the proposed algorithm can solve the MTO-CD synchronization problem effectively. Based on a comprehensive sensitivity analysis, some significant managerial implications have been revealed, which help the decision maker to configure the production resource and warehousing resource in different scenarios.

Closed Shop Scheduling Optimisation using Max-Plus Automata

An appropriate scheduling system is needed in manufacturing activities to minimize production time and costs. Flow shop is one type of production flow that widely used in manufacturing. Based on the demand criteria, it has been known as a scheduling problem called closed shop. This scheduling emphasizes the make-to-stock (MTS) which produces a stock. We take the closed shop scheduling case studies from an existing literature and optimize scheduling using max-plus automata optimum. We compare the result with regular scheduling and the previous result in the literature. We show that the result of max-plus automata optimum scheduling are optimum compared than the existing regular scheduling and the existing previous result of the literature.