Bicriteria robotic cell scheduling

This paper considers the scheduling problems arising in two- and three-machine manufacturing cells configured in a flowshop which repeatedly produces one type of product and where transportation of the parts between the machines is performed by a robot. The cycle time of the cell is affected by the robot move sequence as well as the processing times of the parts on the machines. For highly flexible CNC machines, the processing times can be changed by altering the machining conditions at the expense of increasing the manufacturing cost. As a result, we try to find the robot move sequence as well as the processing times of the parts on each machine that not only minimize the cycle time but, for the first time in robotic cell scheduling literature, also minimize the manufacturing cost. For each 1-unit cycle in two- and three-machine cells, we determine the efficient set of processing time vectors such that no other processing time vector gives both a smaller cycle time and a smaller cost value. We also compare these cycles with each other to determine the sufficient conditions under which each of the cycles dominates the rest. Finally, we show how different assumptions on cost structures affect the results.     

Two-machine flowshop scheduling with flexible operations and controllable processing times

We consider a two-machine flowshop scheduling problem with identical jobs. Each of these jobs has three operations, where the first operation must be performed on the first machine, the second operation must be performed on the second machine, and the third operation (named as flexible operation) can be performed on either machine but cannot be preempted. Highly flexible CNC machines are capable of performing different operations. Furthermore, the processing times on these machines can be changed easily in albeit of higher manufacturing cost by adjusting the machining parameters like the speed and/or feed rate of the machine. The overall problem is to determine the assignment of the flexible operations to the machines and processing times for each operation to minimize the total manufacturing cost and makespan simultaneously. For such a bicriteria problem, there is no unique optimum but a set of nondominated solutions. Using ?-constraint$?\mathrm{-}\mathrm{constraint}$ approach, the problem could be transformed to be minimizing total manufacturing cost for a given upper limit on the makespan. The resulting single criterion problem can be reformulated as a mixed integer nonlinear problem with a set of linear constraints. We use this formulation to optimally solve small instances of the problem while a heuristic procedure is constructed to solve larger instances in a reasonable time.     

Single CNC machine scheduling with controllable processing times to minimize total weighted tardiness

Advanced manufacturing technologies, such as CNC machines, require significant investments, but also offer new capabilities to the manufacturers. One of the important capabilities of a CNC machine is the controllable processing times. By using this capability, the due date requirements of customers can be satisfied much more effectively. Processing times of the jobs on a CNC machine can be easily controlled via machining conditions such that they can be increased or decreased at the expense of tooling cost. Since scheduling decisions are very sensitive to the processing times, we solve the process planning and scheduling problems simultaneously. In this study, we consider the problem of scheduling a set of jobs on a single CNC machine to minimize the sum of total weighted tardiness, tooling and machining costs. We formulated the joint problem, which is NP-hard since the total weighted tardiness problem (with fixed processing times) is strongly NP-hard alone, as a nonlinear mixed integer program. We proposed a DP-based heuristic to solve the problem for a given sequence and designed a local search algorithm that uses it as a base heuristic.     

Software-based tool path evaluation for environmental sustainability

Currently available life cycle assessment (LCA) tools provide only a rough estimation of the environmental impact of different manufacturing operations (e.g. energy consumption). To address this limitation, a web-based and application programming interface (API) based process analysis software tools were developed to estimate the energy consumption of a computer numerically controlled (CNC) machine tool operation and to evaluate its environmental impact as a first step towards sustainable manufacturing analysis. Acceleration/deceleration of machine tool axes and the direction of axes movement were considered to estimate the total energy demand and processing time of the machine tool operation. Several tool path generation schemes were tested to analyze the energy consumption and resulting green house gas emission of CNC machine tool operation. It showed that tool path generation schemes affect the amount of energy and the processing time required to machine the same part, and location of the machining resulted in different amount and characteristics of green house gas emission.     

An analysis of cyclic scheduling problems in robot centered cells

The focus of this study is a robot centered cell consisting of m computer numerical control (CNC) machines producing identical parts. Two pure cycles are singled out and further investigated as prominent cycles in minimizing the cycle time. It has been shown that these two cycles jointly dominate the rest of the pure cycles for a wide range of processing time values. For the remaining region, the worst case performances of these pure cycles are established. The special case of 3-machines is studied extensively in order to provide further insight for the more general case. The situation where the processing times are controllable is analyzed. The proposed pure cycles also dominate the rest when the cycle time and total manufacturing cost objectives are considered simultaneously from a bicriteria optimization point of view. Moreover, they also dominate all of the pure cycles in in-line robotic cells. Finally, the efficient frontier of the 3-machine case with controllable processing times is depicted as an example.     

Pure cycles in flexible robotic cells

In this study, an m-machine flexible robotic manufacturing cell consisting of CNC machines is considered. The flexibility of the machines leads to a new class of robot move cycles called the pure cycles. We first model the problem of determining the best pure cycle in an m-machine cell as a special travelling salesman problem in which the distance matrix consists of decision variables as well as parameters. We focus on two specific cycles among the huge class of pure cycles. We prove that, in most of the regions, either one of these two cycles is optimal. For the remaining regions we derive worst case performances of these cycles. We also prove that the set of pure cycles dominates the flowshop-type robot move cycles considered in the literature. As a design problem, we consider the number of machines in a cell as a decision variable. We determine the optimal number of machines that minimizes the cycle time for given cell parameters such as the processing times, robot travel times and the loading/unloading times of the machines.     

Cell control system

FANUC has recently developed a machining cell capable of a wide range of manufacturing activities.

This machining cell consists of a Computer Numerically Controlled (CNC) machine tool, an industrial robot and monitoring units. Any number of these cells can be grouped together in a factory to create a highly effective manufacturing system.

This paper outlines the Cell Control System using distributed control and integrated processing.     

A stochastic model for the analysis of a two-machine flexible manufacturing cell

This paper presents a stochastic model to determine the performance of a flexible manufacturing cell (FMC) under variable operational conditions, including random machining times, random loading and unloading times, and random pallet transfer times. The FMC under study consists of two machines, pallet handling system, and a loading/unloading robot. After delivering the blanks by the pallet to the cell, the robot loads the first machine followed by the second. Unloading of a part starts with the machine that finishes its part first, followed by the next machine. When the machining of all parts on the pallet is completed, the handling system moves the pallet with finished parts out and brings in a new pallet with blanks. A model with these characteristics turns out to be a Markov chain with a transition matrix of size 5n+3, where n is the number of parts on the pallet. In this paper, we present exact numerical solutions and economic analysis to evaluate FMC systems, to determine optimal pallet capacity and robot speed that minimize total FMC cost per unit of production.     

Pure cycles in two-machine dual-gripper robotic cells

We consider a robotic cell served by a dual-gripper robot that consists of identical CNC machines placed linearly and a material handling robot loading/unloading the machines and transporting the parts between them. Identical parts are to be processed in this system and the CNC machines are capable of performing all the operations that a part requires. We consider the problem of sequencing activities of the robot in order to maximize the throughput rate. As a consequence of the flexibility of the CNC machines, a new class of robot move sequences, named as pure cycles, arises. In a pure cycle, the robot loads and unloads each machine once and each part is processed on exactly one of the machines. Thereby, the problem is to determine the best pure cycle that maximizes the throughput rate. We first determine the feasibility conditions for the pure cycles and prove some basic results that reduces the number of feasible pure cycles to be investigated. We analyze 2-machine robotic cells in detail and prove that five of the cycles among a huge number of feasible pure cycles dominate the rest. We determine the parameter regions in which each of the five cycles is optimal. We also analyze the performance improvement that can be attained by using a dual gripper robot and provide managerial insights.     

A novel methodology for cross-technology interoperability in CNC machining

In CNC part programmes, the lack of standardisation for representing part geometry and semantics of manufacturing operations leads to the necessity for existence of a unique part programme for each machine. Generating multiple programmes for producing the same part is not a value adding activity and is very time consuming. This wasteful activity can be eliminated if users are given the ability to write an NC program for a specific machine and robustly convert the program to syntax suitable for another CNC machine with a different structure. This, cross-technology interoperability, would enable for parts manufactured on old CNC machines using legacy code to be manufactured on new CNC machines by automatically converting the programmes. Every NC programme is written based on various categories of information such as: cutting tool specifications, process planning knowledge and machine tool information. This paper presents an approach for cross-technology interoperability by refining high-level process information (i.e., geometric features on the part and embedded manufacturing resource data) from NC programmes. These refined items of information stored in compliance with the ISO14649 (STEP-NC) standard may then be combined with new manufacturing resource information to generate NC code in a format that is compatible with machines based on different technologies. The authors provide a framework for this process of identification, semantic interpretation and re-integration of information. The focus of this paper is on asymmetric rotational components as the initial application area. To demonstrate the proposed cross-technology interoperability approach, a C-axis CNC turn–mill machine and a 4 axis CNC machining centre have been used with a simple test component.     

Genetic algorithm for balancing reconfigurable machining lines

We consider the problem of designing a reconfigurable machining line. Such a line is composed of a sequence of workstations performing specific sets of operations. Each workstation is comprised of several identical CNC machines (machining centers). The line is required to satisfy the given precedence order, inclusion, exclusion and accessibility constraints on the given set of operations. Inclusion and exclusion are zoning constraints which oblige or forbid certain operations to be performed on the same workstation. The accessibility constraints imply that each operation has a set of possible part positions under which it can be performed. All the operations performed on the same workstation must have a common part position. Workstation times are computed taking into account processing and setup times for operations and must not exceed a given bound. The number of CNC machines at one workstation is limited, and the total number of machines must be minimized. A genetic algorithm is proposed. This algorithm is based on the permutation representation of solutions. A heuristic decoder is suggested to construct a solution from a permutation, so that the output solution is feasible w.r.t. precedence, accessibility, cycle time, and exclusion constraints. The other constraints are treated with a penalty approach. For a local improvement of solutions, a mixed integer programming model is suggested for an optimal design of workstations if the order of operations is fixed. An experimental evaluation of the proposed GA on large scale test instances is performed.     

面向智能制造加工的虚拟调试系统开发与应用

为了解决智能制造加工系统的调试成本高、周期长及风险大等问题,研究了面向智能制造加工的虚拟调试技术。以智能制造加工系统中机器人、PLC、数控车床及加工中心为研究对象,首先通过工业以太网进行组网并与PC机进行通讯,基于OSGI.NET插件框架开发了交互控制软件,将每个设备驱动做成插件,使得每个插件能够实现当前设备的数据采集、监控及控制。并且在RoboDK软件中建立了系统虚拟的3D模型,通过Redis数据库实现了控制设备和虚拟模型之间的信号交互。然后使用了PLC、机器人控制器、数控车床及加工中心控制器对系统3D模型进行虚拟调试,最后通过实验验证了加工系统的有效性。     

Simulation-based machine shop operations scheduling system for energy cost reduction

Owing to the ever increasing requirements in sustainability, manufacturing firms are trying to reduce their energy consumption and cost. In this paper, we propose a simulation-based machine shop operations scheduling system for minimizing the energy cost without sacrificing the productivity. The proposed system consists of two major functions: (1) real-time energy consumption monitoring (through power meters, a database server, and mobile applications) and (2) simulation-based machine shop operations scheduling (through a machine shop operations simulator). First, the real-time energy consumption monitoring function is developed to collect energy consumption data and provide real-time energy consumption status monitoring/electrical load abnormality warnings. Second, the simulation-based machine shop operations scheduling function is devised to estimate the energy consumptions and cost of CNC machines. In addition, an additive regression algorithm is developed to formulate energy consumption models for each individual machine as simulation inputs. The proposed system is implemented at a manufacturing company located in Tucson, Arizona state of USA. The experiment results reveal the effectiveness of the proposed system in achieving energy cost savings without sacrificing the productivity under various scenarios of machine shop operations.     

考虑多成本约束的柔性作业车间制造资源动态分配模型

针对柔性作业车间多周期生产的设备和人力资源的协同分配问题,从成本的视角对其进行研究.综合考虑设备加工成本、人力成本、工件运输成本、库存成本、拖期成本以及外协成本等成本目标,构建考虑多成本约束的柔性作业车间制造资源动态分配模型,设计基于遗传算法的模型求解方法;最后以一个10台设备、10位工人、5个产品、3周期阶段的生产需求构造算例,给出各阶段制造资源优化分配方案和成本结果,验证了模型与算法的有效性.     

Design of a decision support system for machine tool selection based on machine characteristics and performance tests

Economic globalization, together with heightened market competition and increasingly short product life cycles are motivating companies to use advanced manufacturing technologies. Use of high speed machining is increasingly widespread; however, as the technology is relatively new, it lacks a deep-rooted knowledge base which would facilitate implementation. One of the most frequent problems facing companies wishing to adopt this technology is selecting the most appropriate machine tool for the product in question and own enterprise characteristics. This paper presents a decision support system for high speed milling machine tool selection based on machine characteristics and performance tests. Profile machining tests are designed and conducted in participating machining centers. The decision support system is based on product dimension accuracy, process parameters such as feed rate and interpolation scheme used by CNC and machine characteristics such as machine accuracy and cost. Experimental data for process error and cycle operation time are obtained from profile machining tests with different geometrical feature zones that are often used in manufacturing of discrete parts or die/moulds. All those input parameters have direct impact on productivity and manufacturing cost. Artificial neural network models are utilized for decision support system with reasonable prediction capability.     

Modelling and implementing circular sawblade stone cutting processes in STEP-NC

The paper presents a STEP-NC compliant implementation of circular sawblade stone cutting machining processes. Although some stone machining processes has been already covered in the STEP-NC research and standardization initiatives (as for instance stone machining through stone milling machines), there have not been yet, however, any detailed model proposal to cover circular sawblade stone cutting operations. Sawblade cutting technology for stone parts have several specific parameters with no clear equivalent technologies as defined in milling, turning, etc. The paper reviews main characteristics of the circular sawblade stone cutting machining operations, and proposes a STEP-NC extended model based on the selection and definition of new features and on the modelling of these stone cutting operations. The resulting model is the base for the development of the STEP-NC stone cutting CAM and CNC machine. The machine architecture is designed to be able to react to changes in the machining conditions, very common in this technology. The system is based on the definition of features to be communicated to the controller. The controller has the objective of machining the features, and it is able to re planning, on real time, the work to get them despite changing conditions in the stone or in the disc.     

差分进化算法求解带批处理机的机器人制造单元调度问题

机器人制造单元是智能制造系统的主要载体,研究机器人制造单元的生产调度问题对于提高智能制造系统的生产效率有着重要作用.对此,研究带批处理机的混合流水线机器人制造单元调度问题.首先,针对机器人制造单元与批处理机的生产特性,建立数学优化模型;其次,设计差分进化算法对其进行求解,提出染色体组编码的概念,求解该问题的染色体组由两个染色体构成,第1条染色体确定工件在每个工序选择的机器,第2条染色体确定加工顺序以及机器人的搬运顺序;然后,设计差分变异、交叉以及选择操作;最后,进行数值实验,结果证明,针对带批处理机的机器人制造单元调度问题,差分进化算法能缩短完工时间,得到更好的解.     

Decision support for unrelated parallel machine scheduling with discrete controllable processing times

In a manufacturing or service system, the actual processing time of a job can be controlled by the amount of an indivisible resource allocated, such as workers or auxiliary facilities. In this paper, we consider unrelated parallel-machine scheduling problems with discrete controllable processing times. The processing time of a job is discretely controllable by the allocation of indivisible resources. The planner must make decisions on whether or how to allocate resources to jobs during the scheduling horizon to optimize the performance measures. The objective is to minimize the total cost including the cost measured by a standard criterion and the total processing cost. We first consider three scheduling criterions: the total completion time, the total machine load, and the total earliness and tardiness penalties. If the number of machines and the number of possible processing times are fixed, we develop polynomial time algorithms for the considered problems. We then consider the minimization problem of the makespan cost plus the total processing cost and present an integer programming method and a heuristic method to solve the studied problem.     

Parallel machine match-up scheduling with manufacturing cost considerations

Many scheduling problems in practice involve rescheduling of disrupted schedules. In this study, we show that in contrast to fixed processing times, if we have the flexibility to control the processing times of the jobs, we can generate alternative reactive schedules considering the manufacturing cost implications in response to disruptions. We consider a non-identical parallel machining environment where processing times of the jobs are compressible at a certain manufacturing cost, which is a convex function of the compression on the processing time. In rescheduling it is highly desirable to catch up the original schedule as soon as possible by reassigning the jobs to the machines and compressing their processing times. On the other hand, one must also keep the manufacturing cost due to compression of the jobs low. Thus, one is faced with a tradeoff between match-up time and manufacturing cost criteria. We introduce alternative match-up scheduling problems for finding schedules on the efficient frontier of this time/cost tradeoff. We employ the recent advances in conic mixed-integer programming to model these problems effectively. We further provide a fast heuristic algorithm driven by dual prices of convex subproblems for generating approximate efficient schedules.     

A multi-regional computation scheme in an AR-assisted in situ CNC simulation environment

Computer numerical control (CNC) simulation systems based on 3D graphics have been well researched and developed for NC tool path verification and optimization. Although widely used in the manufacturing industries, these CNC simulation systems are usually software-centric rather than machine tool-centric. The user has to adjust himself from the 3D graphic environment to the real machining environment. Augmented reality (AR) is a technology that supplements a real world with virtual information, where virtual information is augmented on to real objects. This paper builds on previous works of integrating the AR technology with a CNC machining environment using tracking and registration methodologies, with an emphasis on in situ simulation. Specifically configured for a 3-axis CNC machine, a multi-regional computation scheme is proposed to render a cutting simulation between a real cutter and a virtual workpiece, which can be conducted in situ to provide the machinist with a familiar and comprehensive environment. A hybrid tracking method and an NC code-adaptive cutter registration method are proposed and validated with experimental results. The experiments conducted show that this in situ simulation system can enhance the operator’s understanding and inspection of the machining process as the simulations are performed on real machines. The potential application of the proposed system is in training and machining simulation before performing actual machining operations.