Search strategy for scheduling flexible manufacturing systems simultaneously using admissible heuristic functions and nonadmissible heuristic functions

To scheduling flexible manufacturing system (FMS) efficiently, we propose and evaluate an improved search strategy and its application to FMS scheduling in the P-timed Petri net framework. On the execution of Petri net, the proposed method can simultaneously use admissible heuristic functions and nonadmissible heuristic functions for A^* algorithm. We also prove that the resulting combinational heuristic function is still admissible and more informed than any of its constituents. The experimental results of an example FMS and several sets of random generated problems show that the proposed search method performs better as we expected.     

Deadlock-free scheduling for flexible manufacturing systems using Petri nets and heuristic search

Deadlock-free control and scheduling are two different problems for flexible manufacturing systems (FMSs). They are significant for improving the behaviors of the systems. Based on the Petri net models of FMSs, this paper embeds deadlock control policies into heuristic search algorithm, and proposes a deadlock-free scheduling algorithm to minimize makespan for FMSs. Scheduling is performed as heuristic search in the reachability graph of the Petri net. The searching process is guided by a heuristic function based on firing count vectors of state equation for the Petri net. By using the one-step look-ahead method in the optimal deadlock control policy, the safety of a state is checked. Experimental results are provided to show effectiveness of the proposed heuristic search approach in deadlock-free scheduling for FMSs.     

A constraint programming approach to tool allocation and production scheduling in flexible manufacturing systems

This paper presents a constraint programming (CP) methodology to deal with the scheduling of flexible manufacturing systems (FMSs). The proposed approach, which consists of both a model and a search strategy, handles several features found in industrial environments, such as limitations on number of tools in the system, lifetime of tools, as well as tool magazine capacity of machines. In addition, it tackles the problem in a integrated way by considering tool planning and allocation, machine assignment, part routing, and task timing decisions altogether in the approach. The formulation, which is able to take into account a variety of objective functions, has been successfully applied to the solution of test problems of various sizes and degrees of difficulty.     

The UniSet approach for the programming of flexible manufacturing cells

Flexible manufacturing cells (FMC) may be considered the most significant development in small-batch manufacturing. Setting-up and operating costs of FMC prove to be the most major hindrance to their large-scale implementation and use, particularly by small and medium size industries. Incompatibilities between the different components constituting the cells and the lack of a unified language/approach to programming and coordinating them are cited as the cause of the complexity of setting up and subsequently operating the cells. In order to eliminate these difficulties, a new philosophy for setting-up, programming and control of FMC has been developed. This paper reports the effort to develop this new unified manufacturing instruction set and its environment, called here “UniSet”, its philosophy and some of the components of the UniSet environment. UniSet has been developed as a non-exclusive unified manufacturing instruction set, based on comparisons of the prevailing machine tool and programming primitives. UniSet allows programmers to deal with only one instruction set, if they so desire, in a single coherent environment, rather than numerous machine programming languages. The software system is coded in an object-oriented programming (OOP) language, Smalltalk, and derives its paradigm from the OO philosophy. Test results are also included to demonstrate the applicability of the approach employed.     

Object-oriented and distributed approach for programming robotic manufacturing cells

Flexible manufacturing systems (FMS) are essential for small/medium batch and job shop manufacturing. These types of production systems are used to manufacture a considerable variety of products with medium/small production volumes. Therefore, the manufacturing platforms supporting these types of production must be flexible and organized in flexible manufacturing cells (FMC). Programming FMCs remains a difficult task and is an actual area of research and development. This paper reports an object-oriented approach developed for FMC programming. The work presented was first thought for application in industrial robot manipulators, and later extended to other FMC equipments just by putting the underlying ideas in a general framework. Initially, the motivation for this work was to develop means to add force control to a standard industrial robot manipulator. This problem requires remote access to the robot controller, remote programming and monitoring, as also is required to program and monitor any other FMC equipment. The proposed approach is distributed based on a client/server model and runs on Win32 platforms, i.e., Microsoft Windows and Windows NT. Implementation for the special case of industrial robot manipulators is presented, along with some application examples used for educational, research and industrial purposes.     

Modeling machine loading problem of FMSs and its solution methodology using a hybrid tabu search and simulated annealing-based heuristic approach

In this article, a machine loading problem of a flexible manufacturing system (FMS) is discussed having the bicriterion objectives of minimizing system unbalance and maximizing throughput in the presence of technological constraints such as available machining time and tool slots. A generic 0–1 integer programming formulation with the objective functions and constraints described above has been proposed. A hybrid algorithm based on tabu search and simulated annealing (SA) is employed to solve the problem. The main advantage of this approach is that a short-term memory provided by the tabu list can be used to avoid revisiting the solution while preserving the stochastic nature of the SA method. The proposed methodology has been tested on ten standard problems and the results obtained are compared with those from some of the existing heuristics.     

A novel 0-1 linear integer programming model for dynamic machine-tool selection and operation allocation in a flexible manufacturing system

This paper considers a problem of dynamic machine-tool selection and operation allocation with part and tool movement policies in a flexible manufacturing system (FMS) environment. For this purpose, a novel 0-1 linear integer programming model is presented in such a way that each part and each tool can move during the production phase. It is assumed that there are a given set of tools and machines that can produce different kinds of orders (or part types). The objective of this model is to determine a machine-tool combination for each operation of the part type by minimizing some production costs, such as machining costs, setup costs, material handling costs and tool movement costs. In addition, due to the NP-hard nature of the problem, a new heuristic method based on five simple procedures (FSP) is proposed for solving the given problem, whose performance is tested on a number of randomly generated problems. The related results are compared with results obtained by a branch-and-bound method. It has been found that the proposed heuristic method gives good results in terms of objective function values and CPU times.     

A hierarchic approach to production planning and scheduling of a flexible manufacturing system

The paper deals with the problem of improving the machine utilization of a flexible manufacturing cell. Limited tool magazine space of the machines turns out to be a relevant bottleneck. A hierarchic approach for this problem is proposed. At the upper level, sets of parts that can be concurrently processed (batches) are determined. At the lower levels, batches are sequenced, linked, and scheduled. Methods taken from the literature are used for the solution of the latter subproblems, and an original mixed integer programming model is formulated to determine batches. The proposed methods are discussed on the basis of computational experience carried out on real instances.     

A modular flexible scalable and reconfigurable system for manufacturing of Microsystems based on additive manufacturing and e-printing

Digital manufacturing technologies [1] are gaining more and more importance as key enabling technologies in future manufacturing, especially when a flexible scalable manufacturing of small medium series of customized parts is required. The paper describes a new approach for design manufacturing of complex three dimensional components building on a combination of digital manufacturing technologies such as laminated objects manufacturing, laser and e-printing technologies. The micro component is made up of stacks of functionalized layers of polymer films. The concept is currently developed further in the project SMARTLAM [2], [3], funded by the European Commission. The manufacturing system is based on a flexible, scalable and modular equipment and application features approach which enables the manufacturing of different small size batches without tool or mask making in short time. Different modules can be combined by defined hardware and software interfaces. Avoiding time consumable and difficult programming caused by manufacturing a new conceptual approach a Function-Block Runtime (FORTE) executes generated control application platform-independently and coordinates component module functionalities. The control system is designed to integrate all processes as well as the base platform with features far beyond ordinary PLC systems. One aspect is the use of process data out of the data acquisition system to simulate and optimize the processes. These results are incorporated into the main machine control system. Another aspect is the vision system for flexible quality control and closed-loop positioning control with visual servoing.The paper shows the overall concept of SMARTLAM and exemplarily demonstrates the control system as well as the modular equipment approach by the example of the control system for alignment of different stacks and inspection system.     

Loading flexible manufacturing systems: a heuristic approach

In this study, heuristic algorithms are developed for loading Flexible Manufacturing Systems. The heuristic approach is an efficient way of planning the FMS with multiple nonlinear loading objectives.     

Optimum loading of machines in a flexible manufacturing system using a mixed-integer linear mathematical programming model and genetic algorithm

Machine loading problem in a flexible manufacturing system (FMS) encompasses various types of flexibility aspects pertaining to part selection and operation assignments. The evolution of flexible manufacturing systems offers great potential for increasing flexibility by ensuring both cost-effectiveness and customized manufacturing at the same time. This paper proposes a linear mathematical programming model with both continuous and zero-one variables for job selection and operation allocation problems in an FMS to maximize profitability and utilization of system. The proposed model assigns operations to different machines considering capacity of machines, batch-sizes, processing time of operations, machine costs, tool requirements, and capacity of tool magazine. A genetic algorithm (GA) is then proposed to solve the formulated problem. Performance of the proposed GA is evaluated based on some benchmark problems adopted from the literature. A statistical test is conducted which implies that the proposed algorithm is robust in finding near-optimal solutions. Comparison of the results with those published in the literature indicates supremacy of the solutions obtained by the proposed algorithm for attempted model.     

A heuristic approach to batching and scheduling a single machine to minimize setup costs

In this paper we consider the problem of creating batches of parts, to be processed in a flexible manufacturing cell, and scheduling their operations. We consider the case in which the system consists of one machine and at most k parts may be present in the system at the same time. Given that each part requires a sequence of operations, and each operation requires a given tool, the objective is to minimize the total number of setups. We develop a heuristic algorithm for its solution and we present an extensive computational experience.     

Hybrid heuristic search approach for deadlock-free scheduling of flexible manufacturing systems using Petri nets

Based on the Petri net models of flexible manufacturing systems (FMSs), this paper focuses on deadlock-free scheduling problem with the objective of minimizing the makespan. Two hybrid heuristic search algorithms for solving such scheduling problems of FMSs are proposed. To avoid deadlocks, the deadlock control policy is embedded into heuristic search strategies. The proposed algorithms combine the heuristic best-first strategy with the controlled backtracking strategy based on the execution of the Petri nets. The scheduling problem is transformed into a heuristic search problem in the reachability graph of the Petri net, and a schedule is a transition sequence from the initial marking to the final marking in the reachability graph. By using the one-step look-ahead method in the deadlock control policy, the safety of a state in the reachability graph is checked, and hence, deadlock is avoided. Experimental results are provided and indicate the effectiveness of the proposed hybrid heuristic search algorithms in solving deadlock-free scheduling problems of FMSs. Especially, the comparison against previous work shows that both new algorithms are promising in terms of solution quality and computing times.     

Optimal job sequence determination and operation machine allocation in flexible manufacturing systems: an approach using adaptive hierarchical ant colony algorithm

In this paper, an Adaptive Hierarchical Ant Colony Optimization (AHACO) has been proposed to resolve the traditional machine loading problem in Flexible Manufacturing Systems (FMS). Machine loading is one of the most important issues that is interlinked with the efficiency and utilization of FMS. The machine loading problem is formulated in order to minimize the system unbalance and maximize the throughput, considering the job sequencing, optional machines and technological constraints. The performance of proposed AHACO has been tested over a number of benchmark problems taken from the literature. Computational results indicate that the proposed algorithm is more effective and produces promising results as compared to the existing solution methodologies in the literature. The evaluation and comparison of system efficiency and system utilization justifies the supremacy of the algorithm. Further, results obtained from the proposed algorithm have been compared with well known random search algorithm viz. genetic algorithm, simulated annealing, artificial Immune system, simple ant colony optimization, tabu search etc. In addition, the algorithm has been tested over a randomly generated problem set of varying complexities; the results validate the robustness and scalability of the algorithm utilizing the concepts of ‘heuristic gap’ and ANOVA analysis.     

基于Petri网的柔性制造系统调度控制模型

给出了自顶向下构造柔性制造系统(FMS)Petri网模型的方法,提出了随机创建指定数目满足指定条件的测试模型的算法,并给出程序仿真运行的演算规则。在此基础上实现了基于Petri网FMS分析与调度仿真软件平台,该平台可配置性强,容易维护,降低了柔性制造系统方针研究的复杂性。最后给出了该模型实现的模块结构。     

Physical simulation of work scheduling rules in a flexible manufacturing system

This paper describes a physical simulator of an actual flexible manufacturing system. The simulator was used to evaluate work scheduling rules for both part selection and machine selection. Twenty-eight decision rule sets were simulated and evaluated under six major performance criteria.     

A heuristic block-loading algorithm based on multi-layer search for the container loading problem

This paper presents an efficient heuristic block-loading algorithm based on multi-layer search for the three-dimensional container loading problem. First, a basic heuristic block-loading algorithm is introduced. This algorithm loads one block, determined by a block selecting algorithm, in one packing phase, according to a fixed strategy, until no blocks are available. Second, the concept of composite block is introduced, the difference between traditional block and composite block being that composite block can contain multiple types of boxes in one block under some restrictions. Third, based on the depth-first search algorithm, a multi-layer search algorithm is developed for determining the selected block in each packing phase, and making this result closer to the optimal solution. Computational results on a classic data set show that the proposed algorithm outperforms the best known algorithm in almost all the test data.     

Simulation modelling and analysis of part and tool flow control decisions in a flexible manufacturing system

This paper presents the details of a simulation study carried out for analyzing the impact of scheduling rules that control part launching and tool request selection decisions of a flexible manufacturing system (FMS) operating under tool movement along with part movement policy. Two different scenarios have been investigated with respect to the operation of FMS. In scenario 1, the facilities such as machines, tool transporter and part transporter are assumed to be continuously available without breakdowns, whereas in scenario 2, these facilities are prone to failures. For each of these scenarios, a discrete-event simulation model is developed for the purpose of experimentation. A number of scheduling rules are incorporated in the simulation models for the part launching and tool request selection decisions. The performance measures evaluated are mean flow time, mean tardiness, mean waiting time for tool and percentage of tardy parts. The results obtained through the simulation have been statistically analyzed. The best possible scheduling rule combinations for part launching and tool request selection have been identified for the chosen FMS.     

A digital twin-based flexible cellular manufacturing for optimization of air conditioner line

In a personalized and various production mode, the production line needs to be updated quickly to meet market demand. The Optimization of production line is taken as the object. To address the coupling problems, such as unreasonable production line layout, unbalanced process capability, inaccurate logistics distribution and unintelligent equipment testing, a method of flexible cellular manufacturing based on digital twin is put forward. Decoupling based on event mechanisms and multi-objective optimization will be used in the design of methods, which will be continuously optimized in the simulation and will eventually be validated. After the implementation of an air conditioner line, the production capacity increased by 58.3 %, the WIP decreased by 77.8 %, the balance rate of the production line increased by 25.2 %, and the per capita production capacity increased by 29.8 %. The number of operators decreased by 28.3 %. The results show that the optimization method of flexible cellular manufacturing based on digital twin has practical value and guiding significance to improve the efficiency of production line.     

双启发动态规划在水泥煅烧优化控制中的应用

为克服动态规划方法在解决高维问题优化存在的维数灾问题,利用函数近似方法来取得代价函数,通过自学习的方法得到近似动态规划解,适用于复杂、非线性系统的决策优化或控制问题。采用双启发动态规划（DHP）算法用于水泥烧成系统的控制,用神经网络建立评价模块和动作模块对该系统进行优化控制。寻找合适的优化目标函数,由评价模块判断动作的好坏并反馈给动作模块,动作模块给出各参数的调整量。仿真结果显示,系统状态量能够被稳定控制在合理的范围。