An integrated framework for card-based production control systems

Although card-based control systems, such as Kanban and CONWIP, for production processes have been successfully employed, the design discipline does not seem to be clear yet. Therefore, the superiority of one control over the other is controversial. This paper proposes a novel design discipline for card-based control of production processes, by developing the theory of token transaction systems. The theory shows how the three indices represented in Little??s law are decided by the structure of a production process with control cards and deployment of work-in-process (WIP). That is, the relation of WIP, cycle time and throughput on specific sub-network of a production process is clarified. We show how Little??s law should be used in the design of card-based production control systems. As an application of the theory, we resolve complicated result of comparison between Kanban and CONWIP. In doing so, this theory does not restrict the target of analysis to serial production lines, but any shaped processes can be analyzed.     

Development and evaluation of a Basestock-CONWIP pull production control strategy in balanced assembly systems

In this study, a new pull production control strategy called Basestock-Constant Work-in-Process (B-CONWIP) is proposed. It is used to control the flow of materials and information in balanced assembly production systems. This proposed control strategy uses one type of authorization cards called CONWIP card that limits the work-in-process (WIP) in the whole system. It has been applied in a single-product and a mixed-product assembly system balanced by two efficient Genetic algorithms introduced in literature. The performance of this control strategy is compared with another pull production control strategy called Basestock Kanban CONWIP (BK-CONWIP), which is a very promising production control strategy found in literature. The proposed strategy has two control parameters, CONWIP authorization cards and basestock levels while BK-CONWIP has three control parameters Kanban authorization cards, CONWIP authorization cards and basestock levels. The comparison is based on three performance measures average system WIP, percentage of satisfied customer demand (service level) and WIP variation between workstations. The performance of the proposed strategy B-CONWIP and BK-CONWIP is mainly similar in both types of assembly systems when mean demand rates are low with respect to mean service rates with the proposed strategy being easier to control and optimize. On the other hand, when mean demand rates are high with respect to mean service rates; B-CONWIP is preferable if service level is more important, while BK-CONWIP is preferable if WIP level is more important. Regarding WIP variation, it mainly depends on the efficiency of the balancing approach. The more efficient the balancing approach, the less WIP variation. Treating demand as lost instead of backordered results in decreased average system WIP and does not affect service levels in both PCSs. It is also shown that S-KDP is more flexible in dealing with situations of variable product mixes than d-KDP because control parameters can be used by any product which minimizes the effect of the unbalanced systems.     

A performance comparison between Kanban and CONWIP controlled assembly systems

There exists controversy on the superiority of logistics control systems. Kanban and CONWIP systems are focused on and analyzed in this paper. CONWIP is a well-known production control system, and some papers have shown it has better performance than the Kanban system. Our research shows that the Kanban is more flexible for the assembly system under concern with respect to a given objective than the CONWIP. In some cases, if the number of kanbans at each manufacturing/assembling station is optimally set, Kanban system outperforms CONWIP with a lower average WIP and the same level of throughput. That is, the distribution of kanbans can be an important design parameter of the system. We also propose two different policies to release cards in a CONWIP controlled assembly system, followed by their comparison results.     

时延网络控制系统的稳定性

针对网络控制系统中存在的不确定时延 ,首先讨论了系统的建模问题 .系统中传感器采用时间驱动 ,执行器与控制器采用事件驱动 ,传感器的数据采用单包传输 .假设传输时延小于采样周期 ,网络控制系统可以建模为一类具有不确定性的线性离散时延系统 .利用Lyapunov方法 ,给出了闭环系统渐近稳定的充分条件 ,基于相应的线性矩阵不等式可行解 ,可以求解状态反馈控制律 .最后 ,用仿真例子验证了该方法的有效性     

A multi-agent based agile manufacturing planning and control system

In today’s manufacturing enterprise, the performance of customer service level (e.g., short ordering-to-delivery time, low price) is highly dependent on the effectiveness of its manufacturing planning and control system (MPCS). However, most of the current MPCS, employed the hierarchical planning approach, may have some drawbacks, such as structural rigidity, difficulty of designing a control system, and lack of flexibility. Currently, RFID (Radio Frequency Identification) technology has been applied to enhance the visibility, accountability, track ability and traceability of manufacturing system whenever the accurate and detailed manufacturing information (e.g., raw material, WIP, products in factory and products in the down streams) of products will be followed in real-time basis by RFID technique. In addition, a multi-agent approach may be applied in a distributed and autonomous system which allows negotiation-based decision making. Therefore, the objective of this research is to study the application of RFID technique and multi-agent system (MAS) in developing an agent-based agile manufacturing planning and control system (AMPCS) to respond to the dynamically changing manufacturing activities and exceptions.In AMPCS, RFID-based manufacturing control (R-MC) module plays the role of controlling the manufacturing system in which production items and manufacturing resources attached with RFID tag may actively feedback production status to and receive production and operations schedule from advanced manufacturing planning (AMP) module. In addition, a bidding process and algorithm is developed to generate operations schedule by using the characteristics of MAS. Performance analysis (PA) module is responsible not only for evaluating the scheduling results but also for evaluating the performance of production execution. The development of an AMPCS for an automated manufacturing cell demonstrates that the integration of RFID technique and MAS in developing an agile manufacturing planning and control system can really possess the characteristics of visibility, accountability, track ability, responsiveness, and flexibility in a distributed and dynamic manufacturing system.     

Evaluation of multi-product lean manufacturing systems with setup and erratic demand

The consideration of demand variability in Multi-Product Lean Manufacturing Environment (MPLME) is an innovation in production system engineering. Manufacturing systems that fail to recognise demand variability generate high Work-In-Process (WIP) and low throughput in MPLME. In response to demand variability, organisations allocate large quantities of Production Authorisation Cards (PAC). A large proportion of PAC results in a high WIP level. However, the Shared Kanban Allocation Policy (S-KAP) allows the distribution of PAC among part-types, which minimises WIP in MPLME. Nevertheless, some existing lean manufacturing control strategies referred as Pull Production Control Strategies (PPCS) that have shown improved performance in single-product systems failed to operate S-KAP. The recently developed Basestock–Kanban-CONWIP (BK-CONWIP) strategy has the capability of minimising WIP while maintaining low backlog and volume flexibility. This paper investigates the effects of erratic demand on the performance of PPCS in MPLME. It is shown that S-KAP BK-CONWIP outperforms other PPCS. Finally, it is feasible to design quick-response PPCS for MPLME under erratic demand.     

Effect of product mix on multi-product pull control

Product mix influences the performance of pull production control strategy in multi-product manufacturing systems. The complexity of product mix on the performance of a manufacturing system is primarily based on the characteristics of the demand and production control strategies. Demands are mainly characterised by volume and product-type while production control strategy is characterised by material release time, part flow, inventory control and throughput times. In multi-product systems, pull production control strategy operates dedicated or shared Kanban allocation policy. This paper examines the performance of the Generalised Kanban Control Strategy (GKCS), Extended Kanban Control Strategy (EKCS) and Basestock Kanban-CONWIP (BK-CONWIP) control strategy operating Shared Kanban Allocation Policies (S-KAP) or Dedicated Kanban Allocation Policies (D-KAP) for a healthcare parallel/serial assembly line with setup times. A simulation based multi-objective optimisation technique was adopted to examine the effect of different product mixes on the strategies and policies. A ranking and selection technique for multiple systems was used to screen the performance of the strategies. It was shown that product mix variability in a system influence the inventory levels of the pull control strategies examined. However, the performances of the strategies vary with strategies operating S-KAP having better inventory control than strategies operating D-KAP. Similarly, BK-CONWIP outperformed its alternatives.     

Analysis of event-driven controllers for linear systems

Most research in control engineering considers periodic or time-triggered control systems with equidistant sample intervals. However, practical cases abound in which it is of interest to consider event-driven control in which the sampling is event-triggered. Although there are various benefits of using event-driven control like reducing resource utilization (e.g., processor and communication load), their application in practice is hampered by the lack of a system theory for event-driven control systems. To provide a first step in developing an event-driven system theory, this paper considers an event-driven control scheme for perturbed linear systems. The event-driven control scheme triggers the control update only when the (tracking or stabilization) error is large. In this manner, the average processor and/or communication load can be reduced significantly. The analysis in this paper is aimed at the control performance in terms of practical stability (ultimate boundedness). Several examples illustrate the theory.     

Manifold learning based rescheduling decision mechanism for recessive disturbances in RFID-driven job shops

In actual manufacturing processes, some unexpected disturbances, called as recessive disturbances (e.g., job set-up time variation and arrival time deviation), would gradually make the original production schedule obsolete. It is hard for production managers to perceive their presences. Thus, the impact of recessive disturbances can not be eliminated by rescheduling in time. On account of this, a rescheduling decision mechanism for recessive disturbances in RFID-driven job shops is proposed in this article, and a manifold learning method, which reduces the response time of manufacturing system, is applied in the mechanism to preprocess manufacturing data. The rescheduling decision mechanism is expected to answer the questions of whether to reschedule, when to reschedule, and which rescheduling method to be used. Firstly, RFID devices acquire the actual process completion time of all work in process (WIPs) at every WIP machining process completion time. Secondly, recessive disturbances are quantified to time accumulation error (TAE) which represents the difference between actual process completion time and planned process completion time. Lastly, according to the TAE and production managers’ experience, the rescheduling decision mechanism selects a proper rescheduling method to update or repair the original production schedule. The realization algorithms of rescheduling decision mechanism includes: (1) supervised locally linear embedding. (2) General regression neural network. (3) Least square-support vector Machine. Finally, a numerical experiment is used to demonstrate the implementation procedures of the rescheduling decision mechanism.     

Developing a framework for performance analysis of a production process controlled by Kanban and CONWIP

In this paper, we develop a framework for comparing pull production control systems, which defines and contains of activity interaction diagram and critical circuit. Kanban and CONWIP control systems are focused on and analyzed. We show that, for a production process controlled by Kanban or CONWIP, the critical circuit determines performance measures, such as the system throughput. Initial inventories as well as card distribution are important parameters that decide the critical circuit, and hence influence the system performance. In addition, by means of our proposed framework, we provide comparative results between Kanban and CONWIP control systems in tree-shaped production processes and serial production lines as sample applications of the framework. The results show that determining the certain superior production control system depends on the system parameters, such as the process structure, initial values and processing times.     

A job assignment model for conveyor-aided picking system

Due to development and popularity of the information and automation technologies, the traditional logistics industry gradually implements the automation (e.g., sorters) or semi-automation (e.g., conveyors) techniques to support the picking operation in order to save huge labor cost of distribution centers (DCs). As for the semi-automatic picking system using the conveyor system, one of the critical issues is to appropriately assign the items to be picked to each workstation in the conveyor system in order to balance workload of each workstation and to enhance the overall resource utilization of a DC. Traditionally, the job assignment of a conveyor system is conducted by means of empirical rules or arbitrary decision of the planner and the task is usually time-consuming. As for the job assignment of the conveyor-aided picking system, this study develops a model to generate workload-balanced job assignment suggestions to the planner. In the proposed methodology, the expertise of job assignment for conveyor-aided picking system is extracted via interviews in order to derive the empirical rules for conveyor job assignment. After that, the empirical rules are quantitatively converted into empirical indices and the weights of empirical indices can be determined via the historical job assignment records. On the other hand, based on the items denoted in the picking schedule, the candidate job assignment plans are generated randomly or via the exhaustion method. Afterwards, on the basis of the derived empirical indices and corresponding weights, the optimal assignment plan can be determined. In addition to the job assignment algorithm, this study establishes a job assignment system for the conveyor-aided picking system. A real-world case is also presented to verify performance of the proposed methodology. In summary, the job assignment model proposed in this study can significantly reduce the time required for job planning for the conveyor-aided picking system and enhance applicability of the job assignment plans.     

网络诱导随机时延的实时处理对策及程序实现

分析了包含远程网络在内的闭环网络控制系统所有的可能随机时延，从不同网络层次探讨了其发生的机理。结合实际工程实时处理的需求，从远程监控端的角度提出解决网络诱导随机时延问题的一些有效对策，主要包括两方面：(1)估算、测试最佳扫描周期，采用时间驱动方式轮询现场数据；(2)采用事件驱动方式优先响应随机控制命令。将随机时延经程序处理转化为系统可控的时延，弥补了随机时延可能给控制系统性能带来的损失。     

串行饱和生产线模糊控制方法的研究

生产存储控制的任务是按时完成生产计划的前提下,控制生产节奏,尽量降低不必要的库存.为了在保持生产线最大通过率的前提下,达到平均在制品量最少的目的,采用模糊控制技术,对串行饱和生产线进行物料准入控制.在对物料准入控制问题进行简单描述的基础上,详细介绍了模糊控制器的设计.通过实例仿真与CONWIP控制进行了对比,结果表明采用模糊控制可以取得令人满意的效果.     

Optimal control of a class of hybrid systems

We present a modeling framework for hybrid systems intended to capture the interaction of event-driven and time-driven dynamics. This is motivated by the structure of many manufacturing environments where discrete entities (termed jobs) are processed through a network of workcenters so as to change their physical characteristics. Associated with each job is a temporal state subject to event-driven dynamics and a physical state subject to time-driven dynamics. Based on this framework, we formulate and analyze a class of optimal control problems for single-stage processes. First-order optimality conditions are derived and several properties of optimal state trajectories (sample paths) are identified which significantly simplify the task of obtaining explicit optimal control policies     

基于UML-RT的复杂嵌入式系统建模方法及其应用

分析了UML在实时系统设计中的优点和需要解决的主要问题,论述了基于UML RT的实时嵌入式系统设计方法,并且对其进行扩展以支持数据流计算模型的建模,最后以汽车巡航系统为例加以说明。     

基于几何可靠性机器模型的装配系统实时性能分析

装配系统是生产系统的基本结构之一, 广泛应用于汽车、电器、电子产品等实际生产环境中.与传统的串行生产线取得的研究成果相比, 装配系统的研究, 特别是对系统暂态过程的实时性能分析的研究仍然未得到深入探讨.本文针对具有三台几何可靠性机器模型和有限缓冲区容量框架下的装配系统, 首先建立了用于此类系统暂态性能分析的数学模型, 通过马尔科夫方法导出了系统性能分析的解析公式.然后, 提出了一种基于分解的性能评估算法来近似系统的实时性能.具体来说, 本文推导出了用于计算具有三台几何可靠性机器模型的装配系统的实时生产率、消耗率、在制品数量, 以及完成一个生产批次所需时间的解析表达式.最后, 通过数值实验对所提出算法的准确性进行验证.     

Two machine flow shop scheduling problem with weighted WIP costs

This paper considers two new machine flow shop scheduling problems where the objective is to minimize the total WIP (work-in-process) cost. In this type of problems, the unit time WIP cost increases or decreases as a job passes through a series of stages in the production process.     

Regional pole assignment for uncertain delta-operator systems

The pole assignment in a specified disk by state feedback for uncertain delta-operator systems is studied. By making use of algebra Riccati equations, a sufficient and necessary condition of pole assignment for a kind of parameter uncertain delta-operator system in a specified disk by state feedback is presented. And the design method of state feedback controller is also developed.The proposed method can unify some previous rehted results of continuous and discrete time systems into the delta framework. The efficiency of the design method is illustrated by a numerical example.     

E-DEVICE: an extensible active knowledge base system with multiplerule type support

This paper describes E-DEVICE, an extensible active knowledge base system (KBS) that supports the processing of event-driven, production, and deductive rules into the same active OODB system. E-DEVICE provides the infrastructure for the smooth integration of various declarative rule types, such as production and deductive rules, into an active OODB system that supports low-level event-driven rules only by: (1) mapping each declarative rule into one event-driven rule, offering centralized rule selection control for correct run-time behavior and conflict resolution, and (2) using complex events to map the conditions of declarative rules and monitor the database to incrementally match those conditions. E-DEVICE provides the infrastructure for easily extending the system by adding: (1) new rule types as subtypes of existing ones, and (2) transparent optimizations to the rule matching network. The resulting system is a flexible, yet efficient, KBS that gives the user the ability to express knowledge in a variety of high-level forms for advanced problem solving in data intensive applications     

Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance

The introduction of modern technologies in manufacturing is contributing to the emergence of smart (and data-driven) manufacturing systems, known as Industry 4.0. The benefits of adopting such technologies can be fully utilized by presenting optimization models in every step of the decision-making process. This includes the optimization of maintenance plans and production schedules, which are two essential aspects of any manufacturing process. In this paper, we consider the real-time joint optimization of maintenance planning and production scheduling in smart manufacturing systems. We have considered a flexible job shop production layout and addressed several issues that usually take place in practice. The addressed issues are: new job arrivals, unexpected due date changes, machine degradation, random breakdowns, minimal repairs, and condition-based maintenance (CBM). We have proposed a real-time optimization-based system that utilizes a modified hybrid genetic algorithm, an integrated proactive-reactive optimization model, and hybrid rescheduling policies. A set of modified benchmark problems is used to test the proposed system by comparing its performance to several other optimization algorithms and methods used in practice. The results show the superiority of the proposed system for solving the problem under study. The results also emphasize the importance of the quality of the generated baseline plans (i.e., initial integrated plans), the use of hybrid rescheduling policies, and the importance of rescheduling times (i.e., reaction times) for cost savings.