Impact of the integration of tactical supply chain planning determinants on performance

In fulfilling customers’ orders, one of the goals of tactical supply chain planning is to satisfy the customers in terms of delivery efficiency, delivery quantity accuracy and on-time delivery. These performance objectives can be impacted by the way firms plan each of the three phases of the supply chain: procurement, production and distribution. Though the link between each of these phases and supply chain performance has been studied in extant literature, very few authors have considered all three phases at the same time. By adopting an integrated approach, this paper therefore aims to study the manner in which, taken together in one model, the planning determinants of the different phases impact on supply chain performance. It is important for managers to understand, from a holistic and integrated perspective, how a given combination of the planning determinants of the supply chain functions impacts positively or negatively on the performance of the supply chain. To carry out this study, this paper starts by proposing an integrated framework that is based on the SCOR model and the customer order decoupling point (CODP), followed by a five-step methodology for tactical supply chain planning. Then, using an analytical model and simulations, and based on a numerical example, it shows how the proposed methodology can be applied in a given decision-making situation. Our results enabled to identify the worst and the best combinations of planning determinants.     

A decision support system for automotive product planning and competitive market analysis

A decision support system (DSS) for automotive product marketing, design and manufacturing in China is presented in this paper. The DSS is developed as a tool to support product planning, competitive market analysis, supply chain analysis and subsequent manufacturing systems planning and deployment. The system consists of a number of automotive related databases which provide information about manufacturers' performance in each market segment as well as production information of all existing market players in the Chinese auto industry. Product planning, one of the key modules of the DSS prototype, is highlighted in this paper. It supports decision makers in determining suitable strategies for market entry by analyzing existing competitors' status, growth estimation of each market segment, and competitive market analysis for new vehicle products. A case study for new market entry is included here to demonstrate the feasibility and effectiveness of the proposed methodology.     

Resource planning for direct fabrication of customized orthopedic implants using EBM technology

Medical innovations and patient expectations are pushing healthcare toward personalized medicine. In orthopedics, the concept of patient-specific implants could be economically realized with the use of additive manufacturing. Knee and hip replacements are some of the most common musculoskeletal procedures performed in the United States. Joint replacement implants are typically offered in standard sizes and geometries. The mass customization of theses prostheses, however, can improve patient outcomes and reduce medical costs. Mass customization is not economically feasible with traditional manufacturing methods because of the high fixed tooling costs for each geometry. The freedom of design offered by additive manufacturing presents a viable production alternative for unique personal geometry. The objective of this paper is to develop two new analytic models that can be used to investigate a complex additive manufacturing supply chain. The focus of the model is to provide planning tools and a methodology for the direct production of customized orthopedic implants using electron beam melting, an additive manufacturing technology. First, a production model for an additive manufacturing-based system is created. Next, resource planning for a single customized implant system is performed using a simulation model. A queuing model is developed for rapid systems analysis. The staffing requirement predictions of the two models align closely for production of a singular, customized implant. A detailed systems analysis of an additive manufacturing supply chain is conducted to illustrate the use of these models. The queueing model is analytically tractable, so it is extended to describe the production of standard and customized versions of multiple implant families.     

Multi-plant production scheduling in SMEs

Traditionally, companies used to view themselves as separate entities and did not devote efforts to collaborate with other echelons of the extended enterprise. This even happened at multi-site companies owning different plants that belonged to the same supply chain. However, manufacturing facilities of the same supply chain should intensively share information and coordinate planning and scheduling tasks in order to get a globally optimized solution. This paper discusses some specific characteristics of the planning and scheduling problem in the extended enterprise including an analysis of a case study, and reviews the available state-of-the-art research studies in this field. Most studies suggest that integrated approaches can have a significant impact on the system performance, in terms of lower production costs, and less inventory levels. The paper provides some conclusions and suggestions of future works.     

Agent-Based Systems for Intelligent Manufacturing: A State-of-the-Art Survey

Agent technology has been considered as an important approach for developing distributed intelligent manufacturing systems. A number of researchers have attempted to apply agent technology to manufacturing enterprise integration, supply chain management, manufacturing planning, scheduling and control, materials handling, and holonic manufacturing systems. This paper gives a brief survey of some related projects in this area, and discusses some key issues in developing agent-based manufacturing systems such as agent technology for enterprise integration and supply chain management, agent encapsulation, system architectures, dynamic system reconfiguration, learning, design and manufacturability assessments, distributed dynamic scheduling, integration of planning and scheduling, concurrent scheduling and execution, factory control structures, potential tools and standards for developing agent-based manufacturing systems. An extensive annotated bibliography is provided.     

大规模定制下多CODP的定位模型及算法

在分析大规模定制系统中单客户订单解耦点（Customer Order Decoupling Point,CODP）生产模式不足的基础上,提出为不同属性的产品设置不同的多CODP的大规模定制生产模式,通过分析企业订单及其产品定制属性,设计多CODP的定位机制及模型,并给出算法。最后以某电动车生产企业为例,验证模型及算法的可行性。     

Study of the performance of multi-behaviour agents for supply chain planning

In today's industrial context, competitiveness is closely associated to supply chain performance. Coordination between business units is essential to increase this performance, in order to produce and deliver products on time to customers, at a competitive price. While planning systems usually follow a single straightforward production planning process, this paper proposes that partners adapt together their local planning process (i.e. planning behaviours) to the different situations met in the supply chain environment. Because each partner can choose different behaviour and all behaviours will have an impact on the overall performance, it is difficult to know which is preferable for each partner to increase their performance. Using agent-based technology, simulation experiments have been undertaken to verify if multi-behaviour planning agents who can change planning behaviours to adapt to their environment can increase supply chain performance. These agents have been implemented in an agent-based planning platform, using a case study illustrating a lumber supply chain. The performance analysis shows that advanced planning systems can take advantage of using multiple planning processes, because of the dynamic context of supply chains.     

Design and planning problems in flexible manufacturing systems: a critical review

This review paper describes the state-of-the-art research on flexible manufacturing systems (FMS) design and planning issues. The emphasis is on presenting research results coming out of the current FMS literature that help the FMS manager in setting up a highly efficient manufacturing system. In addition to that, it discusses relevant research contributions after 1986, that were not part of any of the previous survey papers on operations research models for FMSs. Also, applications of combinatorial optimization approaches to FMS planning problems are adequately exposed in the paper.     

Automated manufacturing system discovery and digital twin generation

The latest developments in industry involved the deployment of digital twins for both long and short term decision making, such as supply chain management, production planning and control. Modern production environments are frequently subject to disruptions and consequent modifications. As a result, the development of digital twins of manufacturing systems cannot rely solely on manual operations. Recent contributions proposed approaches to exploit data for the automated generation of the models. However, the resulting representations can be excessively accurate and may also describe activities that are not significant for estimating the system performance. Generating models with an appropriate level of detail can avoid useless efforts and long computation times, while allowing for easier understanding and re-usability. This paper proposes a method to automatically discover manufacturing systems and generate adequate digital twins. The relevant characteristics of a production system are automatically retrieved from data logs. The proposed method has been applied on two test cases and a real manufacturing line. The experimental results prove its effectiveness in generating digital models that can correctly estimate the system performance.     

An agent-based approach for e-manufacturing and supply chain integration

A major problem facing manufacturing organisations is how to provide efficient and cost-effective responses to the unpredictable changes taking place in a global market. This problem is made difficult by the complexity of supply chain networks coupled with the complexity of individual manufacturing systems within supply chains. Current systems such as manufacturing execution systems (MES), supply chain management (SCM) systems and enterprise resource planning (ERP) systems do not provide adequate facilities for addressing this problem. This paper presents an approach that would enable manufacturing organisations to dynamically and cost-effectively integrate, optimise, configure, simulate, restructure and control not only their own manufacturing systems but also their supply networks, in a co-ordinated manner to cope with the dynamic changes occurring in a global market. This is realised by a synergy of two emerging manufacturing concepts: Agent-based agile manufacturing systems and e-manufacturing. The concept is to represent a complex manufacturing system and its supply network with an agent-based modelling and simulation architecture and to dynamically generate alternative scenarios with respect to planning, scheduling, configuration and restructure of both the manufacturing system and its supply network based on the coordinated interactions amongst agents.     

Production planning and worker training in dynamic manufacturing systems

Production planning is a vital activity in any manufacturing system, and naturally implies assigning the available resources to the required operations. This paper develops and analyzes a comprehensive mathematical model for dynamic manufacturing systems. The proposed model integrates production planning and worker training considering machine and worker time availability, operation sequence and multi-period planning horizon. The objective is to minimize machine maintenance and overhead, system reconfiguration, backorder and inventory holding, training and salary of worker costs. Computational results are presented to verify the proposed model.     

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.     

Setting order promising times in a supply chain network using hybrid simulation-analytical approach: An industrial case study

Supply chain management (SCM) involves the management of material and information flow among the members of chain such as vendors, manufacturing plants and distribution centers. The main processes in supply chain are production planning, control, distribution and logistics. Effective management of all these processes provides the manufacturing companies great advantages in time based competition. In order to gain a competitive edge, firms must be able to deliver their products fast and on-time. This can be managed by better production planning, scheduling and due-date setting. This paper suggests a hybrid approach for setting realistic order due dates for a produce-to-order manufacturing company operating within a supply chain environment. The proposed hybrid approach combines mathematical and simulation modeling to bring together the advantages of both approaches.     

Fuzzy-set-based approach for concurrent constraint set-up planning

Material removal processes are integral parts of many manufacturing systems. They are either primary machining processes or an important part of preparing toolings for subsequent forming and moulding processes. Manufacturing process planning identifies the type of material removal processes and the machining parameters, cutting tools and fixtures needed to generate the features on a part. Previous research in manufacturing process planning has concentrated mainly on the role of features, in the derivation of the associated process and fixture plans. Many computer-aided process planning (CAPP) and computer-aided fixture planning (CAFP) systems derive process and fixture plans from the features on a part, on the basis that these features are context-free. However, manufacturing operations are interdependent processes. In the author's computer-aided set-up planning (CASP) system, a different perspective is adopted. Feature relations form the core of the conceptual structure. These features relations, which are often imprecise, are used in deriving set-up plans. The feature relations, which may be due to geometrical constraints, tolerance requirements, etc., are modelled using fuzzy sets and fuzzy relations. This paper presents the various feature relations considered in the present system and proposes a practical planning algorithm for set-up planning.     

A relationship framework and application in between strategy and operational plans for manufacturing industry

The objective of this paper is to develop a system that calculates a company’s strategic manufacturing performance using indicator values of competitive priorities classified according to manufacturing players and their weights and to determine strategic operations plans to guide short-term decisions based on performance and indicator values. A framework is designed that measures strategic manufacturing strength and links these competitive priorities to manufacturing strategy to plan operations that are compatible with the manufacturing strategy. This framework is applied in a panel furniture company. Quantitative data are obtained from Enterprise Resource Planning database. This work provides a new, more structured methodology with greater quantification and new insights. It is hoped that this decision support system helps that managers of a company in their strategic operations plans decision-making as they develop manufacturing capabilities against competitors. This study eliminates several gaps between the academic literature and current management practice, suggesting that researchers should consider the impact of theory on the process of strategy operations planning. It also offers a way for organizations with respect to determine strategy operations planning according to their current performance measurement systems. This study includes a different approach than those described in the literature because it includes a conceptual model, novel methods used in performance calculation and decision-making related to strategic operations plans.     

Operations Research Techniques in Manufacturing Planning and Control Systems

This paper investigates the possible uses for operations research (OR) models and techniques in manufacturing planning and control (MPC) systems. We discuss various MPC problems where OR can be applied and the potential inclusion of such models in computer-aided MPC systems. It is found that even though the use of OR techniques in current standard MPC packages is rather restricted, there is a potential for utilizing more OR techniques in computer-aided MPC systems, at least in theory. In practice, OR-related techniques are more often developed as stand-alone systems for decision support as a complement to the MPC system. In this paper, specific OR techniques are discussed for specific MPC problems in terms of applicability and the appropriate type of software solution; none at all, stand-alone system or integrated part of the MPC system.     

基于扩展状态任务网的制造供应链计划

制造供应链计划是制造供应链管理的关键问题,它不仅需要分配生产任务和控制库存,还需要解决不同工厂(企业)间的运输配套问题.为统一描述具有复杂产品生产过程(包括装配型、分解型和多输入多输出型等)的生产任务、存储任务和不同模式(包括单种物料独立运输模式和多种物料组合运输模式)的运输任务,提出了扩展状态任务网(extended state task network,简称ESTN).扩展状态任务网用比例转化任务统一描述生产任务、存储任务和单种物料独立运输任务,用虚比例转化任务和组合移动任务共同描述多种物料组合运输任务.应用扩展状态任务网,meta启发式方法在求解制造供应链问题时更容易编码和操作.为求解基于ESTN的制造供应链计划模型,提出了具有多样性检测的参考解集更新策略与分散性解变异策略的路径重连算法.路径重连算法维护一个由高质量解(精英解)组成的参考解集,将一个向导精英解的属性逐步引入一个起始精英解而形成的中间解序列(路径),并用此中间解序列更新参考解集以获得进化.计算实例表明,该路径重连算法比标准遗传算法、标准Tabu搜索算法以及普通路径重连算法能够获得更好的解,证明了多样性检测对参考解集更新的关键作用以及分散性解变异策略在提高解的质量上的能力.     

Design and manufacturing of sheet-metal parts: Using features to aid process planning and resolve manufacturability problems

This paper describes an integrated system for the design and production of sheet-metal parts. We have identified some important features for the sheet-metal bending process. These features are automatically generated as the design progresses. After the designs are complete, our automatic process planning system uses the features and generates new ones to aid the production of plans with near-minimum manufacturing costs. Finally, these plans are used to produce parts on an automatic bending system.Once a plan is generated, it can be used to manufacture the part, and to provide feedback to design and other factory systems. The application of features and the potential feature interaction problems are discussed. Several key manufacturing problems are also considered and the result of planning is used to resolve these problems. By solving these feature interaction problems and often practical manufacturing issues, we are able to plan and manufacture the majority of the parts we have tested less than one hour after the flat patterns are prepared.     

Design of expert systems for integrated production automation

An approach to the design of expert systems for integrated production automation is presented. The major components in an integrated manufacturing system consist of corporate planning, marketing planning, research and development, engineering design, production planning, manufacturing, warehousing, and product distribution. These components are linked by management information flow, technology information flow, as well as materials flow. An intelligent computer is used to integrate information flow and to control materials flow. This paper discusses characteristics of the future factory, elements of knowledge based systems, and the design of computer based expert systems for production planning, for engineering design, and for integrated manufacturing.     

ERP and SCM systems integration: The case of a valve manufacturer in China

Many modern organizations integrate enterprise resource planning (ERP) and supply chain management (SCM) systems, as they work in a complementary fashion. This often results in technical and organizational challenges. Neway, a Chinese organization, recently went through this complex process. This required efficient procurement and management of hardware, software, and human resources for successful completion. The integrated system was found to improve operations, foster a paperless environment, and provide efficient inventory tracking and picking. It also had several tangible benefits, including reduced lead time and improved inventory accuracy. ERP and SCM systems integration is still a novel concept for a Chinese manufacturing organization. Our case study details the organization's experience, identifies challenges that were faced, and describes solutions adopted to overcome them.