Collaborative plan exchange: significant reinforcement for contract net based distributed manufacturing systems

Contract net protocol had been popularly employed in distributed manufacturing systems. However, it provides almost no guarantee of robustness and optimization of performance. In this paper a method called collaborative plan exchange (CPE) is brought forward as reinforcement for contract net protocol. CPE adds an information exchange process among resource agents to let them get up-to-the-minute information, arrange coherent action, fulfil manufacturing constraints and collaboratively complete tasks. When a disturbance occurs, CPE can inform influenced agents and form new coherent work scheme. Theoretical analysis and experiments indicate that system robustness and performance are improved significantly.     

A pattern-directed approach to flexible manufacturing: A framework for intelligent scheduling, learning, and control

The planning, scheduling, and control of manufacturing systems can all be viewed as problem-solving activities. In flexible manufacturing systems (FMSs), the computer program carrying out these problem-solving activities must additionally be able to handle the shorter lead time, the flexibility of job routing, the multiprocessing environment, the dynamic changing states, and the versatility of machines. This article presents an artificial intelligence (AI) method to perform manufacturing problem solving. Since the method is driven by manufacturing scenarios represented by symbolic patterns, it is referred to as pattern-directed. The method is based on three AI techniques. The first is the pattern-directed inference technique to capture the dynamic nature of FMSs. The second is the nonlinear planning technique to construct schedules and assign resources. The third is the inductive learning method to generate the pattern-directed heuristics. This article focuses on solving the FMS scheduling problem.In addition, this article reports the computation results to evaluate the utility of various heuristic functions, to identify important design parameters, and to analyze the resulting computational performance in using the pattern-directed approach for manufacturing problem-solving tasks such as scheduling.     

Generation of optimal control policy for flexible manufacturing cells: A Petri net approach

For flexible manufacturing cells (FMCs), the major control problem is to determine the optimal part routeing and machines dispatching policy. In this research, we present a methodology for generating optimal operating strategies for FMCs. The methodology is built on two techniques: stochastic timed Petri net (STPN) and Markov decision process (MDP). The operating strategy devised with the proposed methodology is deadlock-free and provides the best performance given a set of system parameters (machines, parts, machining times, etc.). Generation of programmable logic controller (PLC) codes is greatly facilitated as the generated strategy can be mapped directly to a ladder diagram representing the PLC code. The objective of real-time optimal control could then be achieved with this type of controller. An example is provided to illustrate the methodology.     

The AAMI contract approach to standards development.

In summary, the AAMI approach enables the FDA to utilize all available resources needed to identify critical characteristics that should be subjected to standards; to develop rationale for those parameters that should not be subjected to standards; and to develop standards in those areas where standards should be developed. During the process, appropriate checks and balances are available because of AAMI's multidisciplinary approach, which is not available using other approaches. The AAMI approach is extremely participatory and, consequently, will result in the production of a standard that will be acceptable to the largest number of people without compromising critical safety and efficacy considerations.     

A distributed internet-based framework for manufacturing planning

Manufacturing organizations worldwide are re-inventing their product development practices in an effort to satisfy changing customer requirements. In the context of these changes influencing the manufacturing community, there is a need to develop frameworks, architectures, and methods to facilitate the creation, implementation, and functioning of virtual enterprises (VEs). This paper presents an Internet-based framework, which supports distributed process planning activities in the context of a VE. Typically, in a VE, the enterprise partners are distributed, and possess diverse skills and heterogeneous software resources, which employ heterogeneous computing platforms. Using the developed approach, physically distributed product development partners can collaborate virtually via the Internet and integrate their life-cycle product development activities through seamless information exchange. In this framework, the distributed manufacturing resources communicate with each other via the Internet inter-ORB protocol (IIOP) using an object request broker (ORB) at each distributed site.     

基于阈值和可用度的合同网协议改进方案研究

针对合同网协议在解决大规模多智能体系统的任务分配问题时所表现出的协商效率低、信息量大等不足,提出了一种基于投标阈值和可用度的合同网协议改进方案.该方案对参与者的投标数量设置了阈值,以限制其不必要的投标,并通过最大化参与者接受适当数目的任务授权的概率来确定阈值;给出了当参与者能力为任何值时均适用的可用度定义,并将其引入到发起者评价过程中,与任务完成质量加权综合,形成新的标书评价函数;并基于系统中总任务数和总能力值的分析,得到可用度权重的计算公式.模拟实验结果表明,该改进方案能有效地提高大规模多智能体系统中合同网协议的性能.     

A life-cycle approach to automation information management in the process industries

This paper presents an overview of the problems and possible solutions for automation information management and utilization in the process industries. The process plant life-cycle model is introduced and the cost structure of process automation investments is reviewed in this context. The general trends in process industry and developments in automation technologies are described and their effects are discussed. The advances in engineering CAD systems and their usability in solving the information management needs over the lifetime of process plants is assessed. This paper also presents one application of advanced engineering CAD system for automation information management in an oil refinery.     

A knowledge-based blackboard framework for stamping process planning in progressive die design

It is widely accepted that stamping process planning for the strip layout is a key task in progressive die design. However, stamping process planning is more of an art rather than a science. This is in spite of recent advances in the field of artificial intelligence, which have achieved a lot of success in incorporating built-in intelligence and applying diverse knowledge to solving this kind of problem. The main difficulty is that existing knowledge-based expert systems for stamping process planning lack a proper architecture for organizing heterogeneous knowledge sources (KSs) in a cooperative decision making environment. This paper presents a knowledge-based blackboard framework for stamping process planning. The proposed approach speeds up the progressive die design process by automating the strip layout design. An example is included to show the effectiveness of the proposed approach.     

An approach to real-time flexible scheduling

Two types of flexibility are important in manufacturing scheduling in general and in real-time scheduling in particular. The first is flexibility with respect to the criteria that can be considered in the scheduling decisions. The second is flexibility with respect to the trade-off between decision quality and computational burden: that is, the ability to arrive at a solution that makes maximum use of theavailable computational capacity and computation time. This paper describes a procedure which meets the above requirements. The procedure is justified using a theoretical analysis based on probability. Experimental results of the procedure's performance are also presented. The results show that random selection (which is used in the procedure) can play a useful role in the real-time scheduling problem.     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

The use of the Petri net reduction approach for an optimal deadlock prevention policy for flexible manufacturing systems

In a flexible manufacturing system (FMS) with multiple products, deadlocks can arise due to limited shared resources, such as machines, robots, buffers, fixtures etc. The development of efficient deadlock prevention policies, which can optimise the use of system resources, while preventing deadlocks from occurring, has long been an important issue to be addressed. In [1], an optimal deadlock prevention policy was proposed, based on the use of reachability graph (RG) analysis of the Petri net model (PNM) of a given FMS and the synthesis of a set of new net elements, namely places with initial marking and related arcs, to be added to the PNM, using the theory of regions. The policy proposed in [1] is optimal in the sense that it allows the maximal use of resources in the system according to the production requirements. For very big PNMs, the reachability graph of the PNMs becomes very large and the necessary computations to obtain an optimal deadlock prevention policy become more difficult. In this paper, we propose the use of the Petri net reduction approach to simplify very big PNMs so as to make necessary calculations easily in order to obtain an optimal deadlock prevention policy for FMSs. An example is provided for illustration.     

Crops: Implementation of a knowledge-based system to plan and monitor the production of a flexible line

CROPS (Coherent Rules for On-line Production Scheduling) is a general system aimed to plan and to control a flexible manufacturing system. The CROPS system receives production orders on a time-scale of one or two weeks from a medium-range planning (MRP) system. The planning and scheduling of those orders are made using a hierarchical temporal network that allows the easy use of rules which represent expert knowledge and common-sense reasoning. Furthermore, the hierarchical temporal network is flexible enough to take into account unavoidable perturbations occurring during plan execution without the need to replan all operations every time a perturbation occurs. Once the operations are planned, the control system transforms them into orders that are sent to the workshop (or to a simulator). With the help of rules, the control system monitors and diagnoses the execution of the orders using a model that maintains a continuous image of the workshop.     

A knowledge-based system for the strategic control level of robots in flexible manufacturing cells

The strategic control level synthesis for robots is related to a hierarchical robot control problem. The main control problem at the strategic control level is to select the model and algorithm to be used by the lower control level to execute the given robot task. Usually there are several lower control level models and algorithms that can be used by the robot control system for every robot task. Strategic control level synthesis depends on the particular robot system application. In a typical application, when the robot system is used in a flexible manufacturing system for manipulating various part types, the robot tasks executed by the robot system depend on the manufacturing processes in the system. If the robot system is applied in another flexible manufacturing system, dedicated to other manufacturing processes, another set of robot tasks might be needed to perform the necessary operations. Therefore, the quantity and the kind of knowledge required in the system for the strategic control level differ from one application to another. Such a fact creates the appropriate conditions for employing some artificial intelligence techniques. This article describes a knowledge-based system approach to the strategic control level synthesis problem.     

A knowledge-based approach for the task implementation in mechanical product design

Although advances have been made to integrate the CAD system with design knowledge, there are still some barriers to apply the knowledge-based design approach to wide practice. A task implementation method is proposed for the mechanical product design process. The design task implementation model is constructed based on its organized-mode and modularity. Declarative knowledge primitives make up of the kernel composition of design task. It makes the design task more controllable and automatable. Solution of the knowledge primitives is directly used to drive the mechanical product. The proposed module has been developed for Intesolid2.0 system, a mechanical CAD system, and it has been evaluated with a design example of a two-stage gearbox.     

A data-driven multiplicative fault diagnosis approach for automation processes

This paper presents a new data-driven method for diagnosing multiplicative key performance degradation in automation processes. Different from the well-established additive fault diagnosis approaches, the proposed method aims at identifying those low-level components which increase the variability of process variables and cause performance degradation. Based on process data, features of multiplicative fault are extracted. To identify the root cause, the impact of fault on each process variable is evaluated in the sense of contribution to performance degradation. Then, a numerical example is used to illustrate the functionalities of the method and Monte-Carlo simulation is performed to demonstrate the effectiveness from the statistical viewpoint. Finally, to show the practical applicability, a case study on the Tennessee Eastman process is presented.     

A multi-agent RFID-enabled distributed control system for a flexible manufacturing shop

Flexible manufacturing systems are complex, stochastic environments requiring the development of innovative, intelligent control architectures that support flexibility, agility, and reconfigurability. Distributed manufacturing control system addresses this challenge by introducing an adaptive production control approach supported by the presence of autonomous control units that are cooperating with each other. Most of the currently distributed control systems still suffer from lack of flexibility and agility when the product verity is high and is not reconfigured in case of ad hoc events. To overcome this limitation, a drawback of an excessive dependence on up-to-date information about the products and other elements that move within the system is essential. Radio frequency identification (RFID) is a new emerging technology which uses radio frequency waves to transfer data between a reader and movable item for identification, tracking, and categorization purpose. This paper discusses the architecture devised to deploy RFID-enabled distributed control and monitoring system by means of a set of agents that are responsible for the realization of different control and monitoring tasks and for cooperating to enhance agility, flexibility, and reconfigurability of manufacturing system.