Bid construction scheme for job flow time reduction in auction-based fully-distributed manufacturing systems

A manufacturing cell can be modelled using discrete event simulation in order to predict its performance under various combinations of input parameters, related to design issues as well as operation issues. Such models suffer from inherent lack of generality and are useful on a case-by-case basis. Therefore, determination of the best values of design and operation parameters in combination cannot be performed rigorously, but only on an experimentation basis. This work proposes a systematic procedure for optimisation. The final stage is an optimisation procedure using a genetic algorithm which uses the classic genetic operators tuned with due care to avoid local maxima of the fitness function. The actual value of the fitness function corresponding to each breeding case could be obtained by running the discrete event simulation application, but that would make for lengthy response. Therefore, a first stage of the optimising procedure is proposed that calculates the essential part of the fitness function by a neural network metamodel generalising on simulation results. Conditions for successful application of the above procedures are discussed.     

基于 Petri网的柔性制造系统动态优化模型

为解决柔性制造系统的动态优化调度问题,在基于扩展高级全局决策Petri网的柔性制造系统优化模型的基础上,提出了实时一优化切换控制Petri网模型。该模型在柔性制造系统发生加工设备故障、急件插入等异常情况时,自动切换并运行全局优化调度算法,并在系统允许的时间范围内,再切换返回到原有系统状态,按照新的优化结果运行。最后,以实时一优化切换控制Petri网模型与基于遗传的最小平衡算法结合为例,证实了该模型是有效的。     

Development of a plate manufacturing CAD/CAM program for a optimal layout and distributed control system

A Problem of relevant interest to some industries is that of obtaining optimum two-dimensional layout. To solve this proviem, one is given a number of rectangular sheets and an order for a specified number of each of certain types of two-dimensional regular and irregular shapes. The aim is to cut the the shapes out of the sheets in such a way as to minimize the amount of waste produced. A DCS (Distributed Control System) is an integrated system which applies the decentralization concept to a control system handling both sequential and analog control. A DCS performs many operations such as data gathering, data processing, data storing and monitoring the operatin conditions for the operator. IN this paper, we propose a genetic algorithm based on rotation parameters from which the best pattern of layout is found as well as a layout method for better performance time. A DCS for the plate cutting process system, which is performed by a virtual system, is also identified.     

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.     

A multiobjective genetic algorithm for scheduling a flexible manufacturing system

Though the designers of Flexible Manufacturing Systems (FMS) strive to ensure the maximum flexibility in the system, in practice, after the implementation of such systems the operational executives often find it hard to accommodate frequent variations in the part designs of incoming jobs. This difficulty can very well be overcome by scheduling the variety of incoming parts into the system efficiently. In this work an appropriate scheduling mechanism is designed to generate a nearer-to-optimum schedule using Genetic Algorithm (GA) with two different GA Coding Schemes. Two contradictory objectives of the system were achieved simultaneously by the scheduling mechanism. The results are compared with those obtained by different scheduling rules and conclusions are presented.     

一种新的分布式MIMO-OFDM系统同步算法

针对不等周期同步算法多段重复引起的同步峰值模糊的问题,提出了一种适用于多输入/多输出正交频分复用(MIMO-OFDM)系统的定时同步算法,算法在原有的不等周期同步模式(UPSP)算法的基础上对其进行结构的优化,同时利用Zadoff_Chu序列良好的互相关性来提高算法的性能。仿真结果表明,提出的算法在AWGN和多径信道下能有效地进行定时同步,特别是在多径情况下,新算法较UPSP算法能更有效地提高准确定时概率。     

A heuristic algorithm to batching and loading problems in a flexible manufacturing system

Part type selection and machine loading are two major problems in the production planning of flexible manufacturing systems (FMS). The two problems are viewed as selecting subsets from the jobs of part types in a planning horizon and allocating jobs of the subsets among machines. In this paper, in order to develop a practical and efficient approach to solving FMS production planning problems, a heuristic algorithm is suggested that develops heuristic rules with the objective of minimisation of the number of tool changes and minimisation of the imbalance in per machine. To compare the proposed algorithm, a series of computational experiments is done on randomly generated test problems and the results show that the developed algorithm is very simple and efficient.     

A methodology to select optimal system components for computer integrated manufacturing by evaluating synergy

The enormous growth in manufacturing automation has produced a plethora of advanced manufacturing technologies (AMTs) with diverse features. These AMTs could consist of semi- and fully automated systems or equipment. Manufacturing companies are seeking ways to gain a competitive edge over their competitors by investing in AMTs, where the ability to make rational choices among these AMTs is important for success. Integration of AMTs in an enterprise brings many islands of automation into a single database-shared entity. Effective integration by efficient communication links among these AMTs will generate significant benefits across many traditional functional units, eliminate many functional barriers, and provide opportunities to achieve the competitive goals. The effect of synergy caused by the integration of AMTs will have an impact on various functional units of the enterprise. This paper provides a methodology, firstly to identify appropriate technologies for a company based on their strategic focus, and secondly to estimate the functional interrelationships within the framework of a unified approach for the justification of computer integrated manufacturing (CIM). These derived functional interrelationships are utilised to assess the effect of synergy in an integrated enterprise and identify the optimal capital investments in AMTs as system components of CIM.     

A dynamic heuristic-based algorithm to part input sequencing in flexible manufacturing systems for mass customization capability

In the increasingly competitive global markets, enterprises face challenges in responding to customer orders quickly, as well as producing customized products cost-effectively. This paper proposes a dynamic heuristic-based algorithm for the part input sequencing problem of flexible manufacturing systems (FMSs) in a mass customization (MC) environment. The FMS manufactures a variety of parts, and customer orders arrive dynamically with order size as small as one. Segmental set functions are established in the proposed algorithm to apply the strategy of dynamic workload balancing, and the shortest processing time (SPT) scheduling rule. Theoretical analysis is performed and the effectiveness of the algorithm in dynamic workload balancing under the complex and dynamic environment is proven. The application of the algorithm is illustrated by an example. The potential of its practical applications to the FMSs in make-to-order (MTO) supply chains is also discussed. Further research is provided.

Intelligent support system for continuous improvement in a dynamic manufacturing environment

In a dynamic competitive environment where consumer demands are getting more sophisticated and technology advancement is very fast, a firm that can quickly improve its workforce's skill level to match the introduction of advanced manufacturing technology will gain a competitive edge. This paper discusses how expert system technology should be modified and integrated with conventional analytical techniques like statistical estimation, pattern recognition, parameter estimation, etc., to provide on-line assistance to less experienced production operators, as well as to provide off-line support of continuous learning and the accumulation of experiences. A new paradigm that integrates the fault-tree (AND-OR graph) and the flow chart is developed. It is shown how such a paradigm can be applied to various applications in the production process, and how it can play an important role in the continuous learning process which will increase the speed of the workforce's skill improvement and production performance.     

An off-line programming system for robotic drilling in aerospace manufacturing

Off-line programming systems are essential tools for the effective use of robots in the manufacturing environment. This paper presents a dedicated off-line programming system for robotic drilling in aerospace manufacturing. Following a brief introduction of the system architecture, the paper discusses two major problems of off-line programming for robotic drilling, i.e., redundancy resolution and position correction. A new performance index is proposed for the combined requirements of singularity and joint-limit avoidance, followed by a discussion of the redundancy resolution scheme by using numerical optimization at the joint displacement level. A position correction method using measurement data of reference holes is developed for the enhancement of robotic drilling accuracy. Robot programs generated by using the developed system have been tested on a robotic drilling system, and the experimental results are provided.     

Function modules demanded for production control in distributed manufacturing system

This paper deals with the function modules demanded for production control in a distributed cellular manufacturing system. Cells are the distributed components of any manufacturing system. A proposed multipassing distributed simulating scheduling system (MPDSSS) deals with the production control functions regarding process planning (working-cell selection), scheduling, rescheduling, and real-time dispatching. The process planning function aims at selecting a good route for each job. The multipassing scheduling aims at providing a scheduling bidding strategy in a distributed fashion. The rescheduling aims at dealing with the large-effort change of the system with updating the precedence schedule to run in a new manufacturing period. The real-time scheduling deals with the small-effort change of the system with a real-time dispatching rule. All the production controlling functions have been implemented in distributed fashions. A simulation experiment demonstrates that the proposed MPDSSS leads to good results in the following criteria: minimum mean flow time, minimum waiting time, maximum machine utilisation, and minimum imbalance of cell utilisation.Nomenclature {A} grouping set ofA _i - A _i function-identical set of celli - BC _i the weighted bidding cost for the operation in celli - {C} performance criteria set - C _i ith element of {C} - CU _{f avg} average cell utilisation inA _f - CU _{f max} maximum cell utilisation inA _f - CU _i average cell utilisation of celli - CU_max maximum CU _i - CU_min minimum CU _i - {D} dispatching rule base - D _i ith rule in {D} - EFT earliest finishing time - EFT_max maximum EFT - ICU _f the imbalance of cell utilisation inA _f - P _m previously actual system performance for criterionC _m - RC _i rescheduling cost when using ruleD _i - SC _i improvement rate for system cost using ruleD _i - SP _a actual system performance - SP _m preceding simulation performance of theC _m with ruleD _i - SP _p ideally predictable system performance - SPD _a actual system performance deviation - TICU _i total imbalance of cell utilisation using ruleD _i - W weighting factor     

Investigating optimal capacity scalability scheduling in a reconfigurable manufacturing system

Responsiveness to dynamic market changes in a cost-effective manner is becoming a key success factor for any manufacturing system in today’s global economy. Reconfigurable manufacturing systems (RMSs) have been introduced to react quickly and effectively to such competitive market demands through modular and scalable design of the manufacturing system on the system level, as well as on the machine components’ level. This paper investigates how RMSs can manage their capacity scalability on the system level in a cost-effective manner. An approach for modeling capacity scalability is proposed, which, unlike earlier approaches, does not assume that the capacity scalability is simply a function of fixed increments of capacity units. Based on the model, a computer tool that utilizes a genetic algorithm optimization technique is developed. The tool aids the systems’ designers in deciding when to reconfigure the system in order to scale the capacity and by how much to scale it in order to meet the market demand in a cost-effective way. The results showed that, in terms of cost, the optimal capacity scalability schedules in an RMS are superior to both the exact demand capacity scalability approach and the approach of supplying all required capacity at the beginning of the planning period, which is adopted by flexible manufacturing systems (FMSs). The results also suggest that the cost-effective implementation of an RMS can be realized through decreasing the cost of reconfiguration of these new systems.     

Mathematical programming approach to optimize material flow in an AGV-based flexible jobshop manufacturing system with performance analysis

An automated manufacturing system (AMS) is a complex network of processing, inspecting, and buffering nodes connected by system of transportation mechanisms. For an AMS, it is desirable to be capable to increase or decrease the output with the rise and fall of demand. Such specifications show the complexity of decision making in the field of AMSs and the need for concise and accurate modeling methods. Therefore, in this paper, a flexible jobshop automated manufacturing system is proposed to optimize the material flow. The flexibility is on the multi-shops of the same type and also multiple products that can be produced. An automated guided vehicle is applied for material handling. The objective is to optimize the material flow regarding the demand fluctuations and machine specifications. An illustrative example is presented to test the validity of the proposed mathematical model.     

FIRST: a Petri net-based system for simulation of complex distributed manufacturing systems

FIRST (Flexible Industrial Robotics Simulation Tool) is a software system for the simulation of complex distributed production systems. A synthetic overview of dynamic simulation methodology is presented and the use of advanced tools for modelling (extended Petri nets) and software implementation (logic programming) is illustrated. A detailed examination of FIRST architecture is made and some possible future developments and improvements are suggested. The results of some practical experiences are illustrated as evidence of the most interesting and useful features of FIRST.     

Solving manpower scheduling problem in manufacturing using mixed-integer programming with a two-stage heuristic algorithm

Manpower scheduling problem is one of the key scheduling problems with extensive applications in manufacturing. This paper presents a mixed-integer programming model with a two-stage heuristic algorithm for solving the manpower scheduling problem in the precision engineering industry. Firstly, a mixed-integer programming formulation is developed to model the manpower scheduling problem in this high-mix low-volume manufacturing environment. Secondly, a two-stage heuristic algorithm is proposed where the first stage is deployed to calculate the skill requirements for each shift by considering the jobs, machines, and their production schedule and the second stage is designed to assign operators to the machines by considering the skill set requirements and the operator's expressed preferences. Lastly, the computational results based on problem instances emulating real-world scenarios demonstrated the feasibility and effectiveness of the proposed heuristic.     

柔性装配制造系统中生产优化的Petri网方法

本文在基本Ｐｅｔｒｉ网的基础上,给出了一种进行周期性生产的柔性装配制造系统的模型;同时,针对该系统,给出了一个求稳定需求下最佳生产指量的启发式调度方法。     

A novel optimal assembly algorithm for haptic interface applications of a virtual maintenance system

A virtual maintenance system in a virtual environment can be used to simulate a real-world maintenance system. The efficiency of the simulation depends mainly on the assembly/disassembly task sequence. During simulation, path planning of mechanical parts becomes an important factor since it affects the overall efficiency of the maintenance system in terms of saving energy and time. Therefore, planners must consider the path-planning factors under constraints such as obstacles and the initial/final positions of the parts, as well as the assembly sequence such as number of gripper exchanges and direction changes. We propose a novel optimal assembly algorithm that considers the assembly sequence of mechanical parts and the path-planning factors for a virtual maintenance simulation system. The genetic algorithm is used to determine the optimal sequence of parts to minimize the numbers of gripper exchanges and direction changes, as well as find a repulsive force radius by using the potential field method to generate the shortest optimal distance for transferring each part during the assembly operation. By applying the proposed algorithm to a virtual maintenance system, users can be haptically guided to the optimized assembly solution during mechanical parts assembly operations. This paper was recommended for publication in revised form by Associate Editor Jong Hyeon Park Christiand received a B.Eng. degree in Mechanical Engineering from University of Indonesia in 2006. He then went on to receive his M.Eng. from Gyeongsang National University in 2008. He is currently a member of engineering staff at Electronics and Telecommunication Research Institute (ETRI) in Daejeon, Korea. Jungwon Yoon received the B.S. degree in precision mechanical engineering in 1998 from the Chonbuk National Univ., Korea, and the M. S. degree in the Department of Mechatronics in 2000 from Gwangju Institute of Science and Technology (GIST), Kwangju, Korea, where he received the Ph.D. in 2005. He had worked as a senior researcher in Electronics Telecommunication Research Institute (ETRI), Daejeon, Korea, and a visiting researcher at Virtual Reality Lab, the Rutgers University, U.S.A, from 2001 to 2002. In 2005, he joined the School of Mechanical & Aerospace Engineering, Gyeongsang National University, Jinju, Korea, where he is currently an assistant professor. His research interests include virtual reality haptic devices & locomotion interfaces, and rehabilitation robots.     

The proposed planning method as a parallel element to a real service system for dynamic sharing of service lines

This paper presents a solution to the bottleneck problem with dynamic sharing or leasing of service capacities. From this perspective the use of the proposed method as a parallel element in service capacities sharing is very important, because it enables minimization of the number of interfaces, and consequently of the number of leased lines, with a combination of two service systems with time-opposite peak loads. In this paper we present a new approach, methodology, models and algorithms which solve the problems of dynamic leasing and sharing of service capacities.