水泥电杆搬运栽杆机设计
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以代理人为基础的模拟准时生产物料搬运系统作者:郝启和沈伟明组织:集成制造技术研究所加拿大国家研究委员会摘要:在大多数组装厂资料处理是一个松散的环。Just-in-time准时制(JIT)是一种在正确的地点,正确的时间的管理理念,努力消除生产制造废物的来源。在组装厂我们提出应用JIT原则处理材料。介绍了材料看板作业作为一种有效的手段去控制物理材料和部分工厂物流。实现了一个基于主体的关于AnyLogic仿真原型的使用。在工厂地板,以代理人为基础的弹性方法便于仿真各种假设情况”场景,包括不同的布图设计,客观参数和动态情况。1.介绍 物料处理是一个松散的环境,通常是被忽略的大部分生产工厂。从我们的观察来看,甚至在一个设计良好的流水线,在整个生产线的条件下,在它的布局、流程优化、缓冲、进度、运营、物料搬运仍然有不合理的控制。经理花费了大量的宝贵时间去找出错误的地方然后再合理的布置流程过程。他们没有意识到的物料搬运或交货计划及相关的资源信息(数量和利用的资源,比如叉车和司机)。作为一个结果,材料处理成为主要障碍,导致生产效率低,低效率,低质量的生产体系。准时生产是一种管理理念,可以提高利润和投资回报减少库存,减少浪费,提高产品质量,降低了生产和交付订货至交货的时间,以及减少其他费用(例如那些相关的设置和设备故障的机器)。特别介绍了拉动式,通过看板的控制,使得JIT生产优化生产过程中获益的生产资源的减少。对工厂而言,早就在运行机制下的需求,材料处理也应该采用拉动式,而不是推动式的。基于此,本文提出了基于物料搬运系统拉动式准时生产原则。在这样一个系统中,材料的运输工厂地板被认为是独立完成的任务。物料看板在工厂的地板上,材料被引入作为载体的交货任务是一种有效的手段去控制和平衡的物理处理材料流动。基本方针,是一项任务所产生的联合站生产单元要求占领一个物料看板一样呈交。另一种技术应用于该材料处理系统就是代理。代理技术的演变而来的研究领域是20世纪90年代的分布式人工智能。从它的产生、代理技术被认为是一种很有前途的范式形式下的设计和制造系统(沈伟明等,2001年)。在JIT物料搬运仿真系统中,实现多个代理商,为协同解决问题的环境。例如,每一个交通工具是封装的代理,以便它是可以在自己的参数和行为,如速度、当地的时间表,和相关的调度,路由和冲突化解规则。司机的交通车辆可以关闭一辆汽车从系统承担个人活动或当汽车故障需要修理的时候。此外,运输任务的分配的谈判来完成一个虽然看板调度代理和大量的汽车代理商。这样的能力,该系统能够模拟动态的情况,而且还能得到更多非常准确的信息,是一般的资源的交通工具。这篇文章的其余部分组织如下:第2部分进行了简单的回顾和文学的背景知识;第三节标识本研究样本准时生产物料搬运问题,叙述了其相应的要求提出了一个基于主体的转机;第四节的建筑准时生产物料搬运系统,并讨论了两个主要方面:生产仿真设计和原材料处理模拟。2.技术评论有两种分类的生产控制系统,即拉动式和推动式。原材料需求计划(MRP)系统和看板管理系统都是最常用的,两种实现策略的方法分别是拉式和推式。在推动式生产中,为了缩小不准确的预测的交货期、库存记录,变更后的的生产计划和可疑材料明细表(BOM),一般包含了安全前置时间和安全的系数。然而,在实践中,MRP可能导致中的一个严重问题(见Shirk 1998,Hopp和斯皮尔曼,1996)。库存水平和订货至交货的时间经过放大在整个供应链中,从最终的经销商一直到每个层次的供应商。相反,使用拉动式策略,而不是使用临床应用准时生产系统容量的缓冲库存,以此来避免可能会出现的问题。在反应生产发起真正的客户订单及消除物品从最终的经销商缓冲器触发来补充库存生产上游一层层地耗尽。维修人员孙俐在2004年进行定量比较的表现,MRP和看板为多级、多产品的生产制造系统。为他们的客户,拉策略是有生产设施,产生了许多不同的产品,具有独特的要求和处理的要求,以及设施,使高度工程产品小批量化(即使是独一无二的)。理想的行业应用准时生产生产范围包括汽车,因为它是准时生产概念的起源。汽车工业是具有较低的产品品种、大批量生产。在一个汽车生产线上,虽然有一些物流线用推动式的(有时称为混合生产),如身体车间、喷漆车间,引擎的线条,然而,一旦汽车正在排队得到处理主要的流水线,生产的控制下一个单一的拉动式。缓冲器设置在离生产线的地点靠不确定性物流线发挥作用,更好地优化了主要生产线的生产速率。准时生产的概念和看板不是一开始就有的。首先由丰田在1950年赞助准时生产时开发的,然后1980年在美国被采用。准时生产和精益企业,聚居区,在西方国家,也进化基于准时生产的原则。许多中小企业和一些大公司已经接受了这些概念,像曼莉琼丝、奔驰、普拉特和惠特尼,保时捷和通用电气等。1996年,特和琼斯在他们基于价值的业务系统中,运用丰田模式 提供了周到的扩张。一路上,他们根据他们的行动计划进行新的研究和不断增强的全球化,他们重新分析它们的一些关键案例,研究来自于汽车、航空航天、等制造业的问题。许多的分析像在数学或实验模型的基础上,提出了在解决看板的基础操作计划和控制问题(具体见Berkley和Martin-Vega 1992;,1990)。到目前为止,模拟的方法论的研究选择在多数文献报告。从理论上讲,看板的数量和配置系统中显著地影响看板拉动式系统的性能。而不是优化这些看板安排导致固定数量的看板,马丁斯和Lewandrowski 在1999年提出了一个数学缓冲区的方法,使用一个动态数据计量看板的策略。古普塔和Al-Turki 在1998年的关于性能比较传统看板系统和一个灵活的看板系统(FKS)。通过仿真模型的两个简单的准时生产模型,他们证明了FKS优于在实时制造环境下的传统看板系统,如突然破裂材料处理系统。从应用的角度上说,研究的拉动式系统可划分分为3大类:(1)生产控制;2)存货管理;3)供应链管理。材料处理是主题被先前的研究在文献(见 古普塔和Al-Turki杂志,2002;Askin高庆宇,1999年;Venkataramanaiah等,2001年)。然而,他们都在处理自动资料(确切地说,是线上的库存,属于生产线之间转移问题本身)生产的单元。在这里我们强调的材料并没有提及在制品经过的流水线,确切地说,它是流动的物质供应或部分服从主要生产线。目前为止,还没有已知的文献分析过关于这方面的物料搬运系统。此外,在大多数工厂中,材料存货只是有过关于完全控制下的在企业层面的MRP II系统或看板系统,但不是实在的动态工厂地板。错缺件,零件不交付的,一部分是正确的地点,正确的时间中的常见现象,几乎所有的主流生产工厂,包括通用、福特、纯正的卡车。对于经理而言材料处理是一项令人头痛的问题。生产部经理感到紧张,每天被指责是缺乏控制制造的过程能力。所以,分析物料处理及动态模拟对制造行业会很有帮助。3. 一个简单装配线的物料搬运系统在拉动式生产中,物料搬运系统的模拟是研究的主要目的。一个基于看板材料处理等问题将会被分析,使其符合拉动式生产线。为方便有较容易的理解,选择一个工厂案例作为背景研究问题,如图所示。(图略) 分析物料搬运方式的时候,我们从基础准时生产相似原理提出了一种类似的库存管理: 正确的材料输送是在正确的时间和正确的量从离开库存区到右边的生产现场。在这里,物资运输的工厂被认为是独立完成任务。一项任务需要一个资料看板被递送。在图中,材料的请求信号首先由产生的装配车间发出去的,这部分的材料供应,经过看板,请求被播出了一系列的车辆正常行驶范围内的无线网络,然后通过调节,任务是经车辆和正在交付最后到右边站。 在我们看来,根据系统分析,准时生产的物料搬运基于看板概念并不仅仅是一种纯粹的事件。这一事件系统中,一个事件立即要求系统响应;而经看板比较,根据系统所产生的事件处理,得到仅在获得一个物理对象的物料看板。换句话说,加工物质需求的事件保持,直到系统释放另一种物料看板与该事件是相符的而代替这个看板所有的其他事件。在看板控制机制的基础上,我们认为在资料处理系统是能够达成一个自然平衡的材料要求和运输活动通过精致的安排和管理看板。除了标准函数在一个模拟环境,如离散事件的解,仿真时钟的生成和一个动画的界面,该系统应具有特殊功能模块,试图模型和模拟动力学在工厂的地板上。三个组的功能构成了准时生产物料搬运系统,典型场景生成,模拟器和图形用户界面。典型场景生成保存大量有关各种配置信息: 1)静态场景,如厂房的布置,移动的轨迹,中心部分库存; 2)仿真参数,如变幻莫测的车辆数目和数量的看板。模拟器为核心的软件,它控制了模拟生产和物料搬运过程中双方的过程。每一个交通工具都有一个独立的车辆仿真模块,使自己的决定,包括任务序列,任务时间表,移动控制、装卸操作,如果必要的话还要加上碰撞分析。生产单位仿真是模块来模仿一个简化生产过程中考虑到只有消费和补货的材料或零件的活动。模拟缓冲和循环(产品全生命周期管理的物料看板)。它使两种决策1)配置信号空物料看板物质需求的;2)对车辆的配置。在模拟器系统中的地位、基本模拟设备如定时器和随机数生成器,应提供模拟同步事件或离散事件。图形用户界面应该及时更新图形仿真、系统事件,例如,及时响应用户的要求在任何一种仿真和统计数据。它直接的一个鲜明特点是“准时生产物料搬运模拟”。该仿真系统具有超越传统模拟的功能。其一,其最显著的能力是便于生产的时候重组。例如,装配任务的安排生产电台将调整执行过程中仿真,从而瓶颈处和系统反应,可以不断变化着的。另一个例子是每个组成部分是可控制的,不但在其配置参数,而且在它的行为可控单独(如,每一个汽车能够使时间表,控制地位,选择自己的交货路线)。相比之下,其他仿真系统是在这之前处理了各文件各仿真信号的发射。人们难以分析的动力系统行为也通过改变系统配置在不同的模拟发射。4. 以代理为基础的准时生产物料搬运的模型我们用代理技术的主要是对准时生产的物料搬运仿真系统模型。代理是先进的计算机程序,自主代表它们的用户的行为,在合作和分布式环境中,开放的解决越来越多的复杂问题。在模拟器中有四种类型的代理设计。1)主要控制商(MCA)主要控制商(MCA)负责模拟、仿真终止时,初始化(线程)管理、线程同步。MCA还包括一个定时器和事件发电机及它的主线程。2)车站代理(SA)车站代理(SA)是一种处于运行中的线程模拟物质需求的活动在车站。它是动态的生成和破坏的大脑中主动脉。一个简单生产速度的装配线上,他们所需配件数量一定。所以,同进步的一个生产步伐,物料平衡在电台可能会达到环境保护的要求水平或紧急的水平。在极端的场合,材料可能感到疲惫引起整个装配线停止。3)看板时间表代理公司(KSA)看板调度代理公司(KSA)是一个独立的线程的职责是照顾1)资料要求的优化调度问题的M-看板,(2)转让物料看板到交通工具。动态创建和销毁KSA是由大脑中动脉决定。适用于普通及紧急调度策略。常规调度是实现由议付KSA之间进行,并参与。4)车辆代理(VA)每个看板分配到一个被怀疑是其车辆VA和所服务的VA通过一系列的行动。一辆汽车代理人是能够处理其在当地的时间表,保持其地位,并控制其运动,修理和简历的行动。所有的车辆都产生螺纹或毁坏MCA在同一时间内。5结论基于要求的工业合作伙伴,物料搬运被认为是一个在大多数组装厂中松散的环节。准时制生产是一个普遍范式实施在现今的制造工厂,奋力将生存在一个全球竞争。JIT的原则,提出了一种优化的生产环境和运行机制,减少库存浪费。然而,材料处理的问题,特别是物料或配件供应工厂地板水平,是很少提到的研究文学与实践。在本文中,我们提出一个物料处理仿真系统,应用准时生产的原则。物料看板是一个个体,携带资料的要求,代表着物资运输任务。一个以代理人为基础的模拟环境的设计与实现了一个原型系统使用。材料处理的准时生产基础预计将提出了许多优点,如系统的水平在于优化生产, 在整个工厂地板平衡的交通负荷,获得可管理性的材料上的操纵性能与准确预测和优化运输资源。最大的不同是,该仿真来自别人的灵活性,以代理人为基础的模拟方法,便于各种假设情况场景包括不同的布图设计,客观参数和动态情况,在工厂地板。AN AGENT-BASED SIMULATION OF A JIT MATERIAL HANDLING SYSTEMQi Hao and Weiming Shen Integrated Manufacturing Technologies Institute National Research Council, Canada 800 CoUip Circle, London, Ontario N6G 4X8, Canada qi.hao; weiming.shennrc.gc.caMaterial handling is a loose loop in most assembly plants. Jiist-in-time (JIT) is amanagement philosophy that strives to eliminate sources of manufacturing waste by producing the right part in the right place at the right time. We propose to apply JIT principles to material handling in assembly plants. Material Kanbans are introduced as an effective means to control and balance the physical material/part flow in the plant Jloor. An agent-based simulation prototype is implemented using AnyLogic. The flexibility of the agent-based approach facilitates the simulation of various what-if scenarios including different layout designs, objective parameters and dynamic situations in the plant floor.1. INTRODUCTIONMaterial handling is a loose loop that is generally neglected in most production plants. From our observation, even in a well designed assembly line, in condition that the whole line is optimized in its layout, processes, buffering, scheduling, and operations, material handling is still laid outside of the scope of control. Managers spend their precious time hunting everywhere for missing parts and arranging their deliveries. They are unaware of material handling/delivery schedules and the related resource information (amount and utilization of resources, such as forklifts and drivers). As a result, material handling becomes the major barrier that results in low efficiency, production breakdowns, and low quality of a production system. Just-in-time (JIT) is a management philosophy that could improve profits and return on investment by reducing inventory levels, reducing variability, improving product quality, reducing production and delivery lead times, and reducing other costs (such as those associated with machine setup and equipment breakdown). The pull mechanism, especially introduced by the Kanban control of JIT manufacturing, enables an optimized production process that benefits from the cutting down of production resources. For a plant that already operates under a pull mechanism, material handling should also employ a pull mechanism rather than a MRP-based push mechanism.This paper intends to propose a pull material handling system based on principles in JIT manufacturing. In such a system, materials transportation in the plant floor is considered as individual tasks. Material Kanban (M-Kanban) is introduced as a carrier of delivery tasks which is an effective means to control and balance the physical material handling flow in the plant floor. The main principle behind is that a task generated by a production station (cell) requires the occupation of an M-Kanban to be delivered. Another technology used in this material handling system is agent. Agent technology is evolved from the research domain of Distributed Artificial Intelligence in 1990s. From its emergence, agent technology is widely recognized as a promising paradigm for the next generation of design and manufacturing systems (Shen et al., 2001). In the JIT material handling simulation system, multiple agents are implemented to facilitate a collaborative problem solving environment. For example, each transportation vehicle is encapsulated as an agent so that it is manageable on its own parameters and behaviors, such as velocity, local schedule, and the associated scheduling, routing and conflict resolving ndes. The driver of a transportation vehicle can deactivate a vehicle from the system to take personal activities or when the vehicle malfunctions and needs a repair. Moreover, the allocation of transportation task is accomplished though the negotiation of a Kanban scheduling agent and a number of vehicle agents. With such capacities, the system is able to simulate very dynamic situations and get more accurate information of transportation resources in general.The rest of this paper is organized as follows: Section 2 reviews the background knowledge and literature of this study; Section 3 identifies a sample JIT material handling problem and describes the corresponding requirements; Section 4 proposes an agent-based architecture of the JIT material handling system and discusses two major design aspects: production simulation and material handling simulation; finally. Section 6 draws our conclusions.2. A TECHNOLOGY REVIEWThere are two classifications of production control systems, namely push and pull. Material requirement planning (MRP) systems and Kanban control systems are the two most popular implementations of the push and pull strategies respectively. In a push production, in order to buffer inaccurate forecasts, inaccurate lead times, inaccurate inventory records, variable production schedules or questionable bill of materials (BOMs), MRP generally incorporates safety lead times and safe stocks. However, in practice, MRP may result in a serious problem of excessive inventories (Shirk, 1998; Hopp and Spearman, 1996). Stock levels and lead times are amplified down throughout the supply chain, from the final distributor down to each hierarchy of suppliers.In contrast, using a pull strategy, a JIT system uses underutilized capacity instead of buffer inventories to hedge against problems that may arise. Production is initiated in response to real customer orders and the removal of items from the final distributor buffers triggers production upstream to replenish exhausted inventories layer by layer. Krishnamurthy et al. (2004) quantitatively compares the performance of MRP and Kanban for a multi-stage, multi-product manufacturing system. They reached the conclusion that pull strategies are handicapped for manufacturing facilities that produce a number of different products with distinct demands and/or processing requirements, as well as for facilities that make highly engineered products in small batches (even one-of-a-kind) for their customers. The ideal industries that JIT production applies include automobile because it is where the JIT concept originated. The automotive industry is characterized by low product variety, and high-volume production. In an automotive assembly line, although there are some sub-lines using push strategies (sometime it is called hybrid production), such as the body shop, paint shop, and engine line, however, once cars are lining up to be processed on the main assembly line, the production is under control of a pure pull mechanism. Buffers are set at offline sites of sub-lines to tickle uncertainties and better serve the optimized production rate of the main assembly line.The concepts of JIT and Kanban are never new. JIT were firstly developed by Toyota in the 1950s and adopted in the United States in the 1980s. Lean manufacturing and lean enterprise, proliferating in western countries, are also evolved based on JIT principles. Many small and medium sized businesses have embraced these concepts along with some of the major corporations such as, Mercedes/Benz, Pratt & Whitney, Porsche and General Electric to name a few. Womack and Jones (1996) provide a thoughtful expansion upon their value-based business system based on the Toyota model. Along the way they update their action plan in light of new research and the increasing globalization of manufacturing, and they revisit some of their key case studies from the automotive, aerospace, and other manufacturing industries.Many analytical, mathematical or experimental models are proposed to address the Kanban based operational planning and control issues (Berkley, 1992; Uzsoy and Martin-Vega, 1990). Simulation has been by far the methodology of choice in the majority of studies reported in the literature (Gupta and Al-Turki, 1998). Theoretically, the number of Kanbans and allocation of Kanbans in a system significantly affects the performance of a pull system. Instead of optimization of these Kanban arrangement which leads to a fixed number of Kanbans, Martins and Lewandrowski (1999) proposed a mathematical buffer stocks dimensioning approach using a dynamic kanban strategy. Gupta and Al-Turki (1998) compared the performance of a traditional kanban system (TKS) and a flexible kanban system (FKS). Through the simulation of two simple JIT models, they proved that FKS outperforms TKS under real-time manufacturing environments, such as sudden breakdown of a material handling system.From application point of view, the researches of pull technologies could be classified in three categories: I) production control; 2) inventory management; and 3) supply chain management (Kusiak, 2000). Material handling is a topic being previously researched in the literature (Gupta and Al-Turki, 1998; Askin, 1999; Venkataramanaiah et al., 2001), however, they all deal with the automatic material (specifically, the Work-In-Process, which belongs to the production line itself) transfer problem between production cells. The material we emphasize here does not refer to the WIP going through the assembly line, rather, it is the supply fiow of material or parts subordinating to the main production line. None of known literature touched the topic of material handling from this aspect.Moreover, in most plants, material inventories are only virtually under control of either a MRP II system or a Kanban system at the enterprise level, but not physically at the dynamic plant floor. Missing parts, wrong part delivered, parts not at right place at right time are common occurrence in almost all mainstream production plants, including GM, Ford, and Sterling Truck. Material handling is a frustrating problem faced by production managers. Production managers are feeling nervous everyday and are blamed for lack of ability to control the manufacturing process. As a result, analysis of material handling and dynamic simulation will be of great help to industries.3. MATERIAL HANDLING SPECIFICATION OF A SIMPLIFIED ASSEMBLY LINESimulation of material handling in a pull production setting is the primary purpose of this research. A Kanban-based material handling will be investigated to make it in line with the pull production line. For the convenience of a common understanding, a sample scenario is chosen as the background problem, as shown in Figure 1 (Figure slightly).The JIT-based material handling approach we proposed borrows similar principles from JIT-based production control and JIT-based inventory management in that: the right material is delivered from its inventory to the right production site, at the right time and in the right amount. Here, material transportation in the plant floor is considered as individual tasks. A task requires a material Kanban (M-Kanban) to be delivered. In figure 1, a material request signal is firstly generated by an assembly station running out of a part supply; after occupying a material Kanban, the request is broadcasted to a number of vehicles moving in the scope of a wireless network; then through negotiation, the task is confirmed by a vehicle and being delivered finally to the right station.In our view, JIT material handling based on Kanban concept is not merely a pure event based system. In an event system, an event calls for a system response immediately; while in a Kanban based system, a generated event gets processed only after obtaining a physical object - M-Kanban. In other words, the processing (transportation) of a material requirement event holds until the system releases a M-Kanban and the event is qualified to occupy this free Kanban among all other events. Based on a Kanban control mechanism, we believe that the material handling system is able to reach a natural balancing of material requirements and transportation activities through delicate arrangement and management of Kanbans.In addition to the standard function in a simulation environment, such as discrete event generation, simulation clock generation and an animation interface, this system should have special functional modules that try to model and simulate the dynamics in the plant floor. Three groups of functions make up the JIT material handling system: scenario generation, simulator, and graphical user interface. Scenario generation maintains a large variety of configuration information relating to: 1) static scenario, such as plant layout, moving tracks, and a central part inventory; 2) changeable simulation parameter, such as number of vehicles and number of Kanbans. Simulator is the core of the software in that it controls the simulation of both the production and material handling processes. Each transportation vehicle has a separate vehicle simulation module to make its own decisions, including task sequence, task schedule, moving control, loading andunloading operations, or even collision resolution decisions if necessary. Station simulation is a module to simulate a simplified production process taking into consideration only the consumption and replenishment activities of materials/parts at each station. Kanban Simulation manages buffering and circulation (life-cycle) of M-Kanbans. It makes two kinds of decisions 1) allocation of material requirement signals to empty M-Kanbans; 2) allocation of M-Kanbans to vehicles. In the simulator, basic simulation facilities such as timer and random number generator should be provided to simulate synchronize events or discrete events. Graphical User interfaces are supposed to timely update the graphical simulation, system event, exceptions, etc, and provide timely response upon users requests for any kind of simulation and statistical data.A distinctive feature of the designated JIT material handling simulation is quasi-realism. The proposed simulation system possesses functions that surpass traditional simulations. The most distinguishing one is its ability to facilitate run-time reconfiguration. For example, the arrangement of assembly tasks to manufacturing stations could be adjusted during the execution of a simulation, so that the bottleneck (of the line) and system responses could be constantly changing. Another example is that each component is manageable not only in its configuration parameter, but also controllable in its behaviors individually (for example, each vehicle is able to make schedules, control status, and choose its own delivery route). In contrast, other simulation systems read a batch file before each simulation launch. It is difficult for people to analyze dynamic system behaviors by changing system configurations in separate simulation launches.4. THE AGENT-BASED JIT MATERIAL HANDLING MODELWe use agent technology to model major components in the JIT material handling simulation system. Agents are sophisticated computer programs that act autonomously on behalf of their users, collaborate across open and distributed environments, to solve a growing number of complex problems. There are four kinds of agents designed in the simulator.1) Main Control Agent (MCA) Main Control Agent (MCA) is responsible for simulation initialization, simulation termination, agent (thread) management, and thread synchronization. MCA also includes a timer and an event generator along with its main thread. 2) Station Agent (SA) Station Agent (SA) is a running thread simulating material requirement activities at stations. It is dynamically generated and destroyed by the MCA. A simple production rate of the assembly line is set for all stations to consume their required parts in certain amounts. So, with the progress of one production step, the material balances at stations may reach the requirement levels or the urgent levels. In extreme occasion, materials may be exhausted which causes the whole assembly line to stop. 3) Kanban Schedule Agent (KSA) Kanban Scheduling Agent (KSA) is a separate thread whose role is to take care of 1) the scheduling of material requirements to M-Kanbans, and 2) the assignment of M-Kanbans to vehicles. KSA is dynamically created anddestroyed by the MCA. It applies regular and emergent scheduling strategies. Regular scheduling is fulfilled by the negotiation carried out between KSA and participating VAs. 4) Vehicle Agents (VA) Each Kanban assigned to a vehicle is confirmed by its VA and served by the VA through a series of actions. A vehicle agent is able to handle its local schedule, maintain its status, and controls its movement, repair, and resume actions. The threads for all vehicles are generated or destroyed by the MCA at the same time.5. CONCLUSIONBased on requirements of industrial partners, material handling has been recognized as a loose loop in most assembly plants. Just-in-time is a pervasive paradigm implemented in nowadays manufacturing plants that strive to survive in a global competition. The principles of JIT bring forward an optimized production environment and a mechanism for waste less inventory replenishment. However, material handling problem, especially the material/part supply at the plant floor level, is seldom addressed in research literature and in practices. In this paper, we propose a material handling simulation system that applies JIT principles. Material Kanban is an entity that carries a material request and represents a material transportation task. An agent-based simulation environment is designed and a prototype system is implemented using AnyLogic. Many experiments will be performed based on the simulation model build for this purpose.The JIT-Based material handling is expected to bring forward a number of advantages, such as optimization of stocks levels at production stations / cells, balancing of transportation load in the whole plant floor, obtaining manageability on material handling performance and accurate prediction and optimization of transportation resources. The major difference of this simulation from others is that the flexibility of the agent-based approach facilitates the simulation of various what-if scenarios including different layout designs, objective parameters and dynamic situations in the plant floor.
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