A complexity model for sequence planning in mixed-model assembly lines

Sequence planning is an important problem in assembly line design. It is to determine the order of assembly tasks to be performed sequentially. Significant research has been done to find good sequences based on various criteria, such as process time, investment cost, and product quality. This paper discusses the selection of optimal sequences based on complexity induced by product variety in mixed-model assembly line. The complexity was defined as operator choice complexity, which indirectly measures the human performance in making choices, such as selecting parts, tools, fixtures, and assembly procedures in a multi-product, multi-stage, manual assembly environment. The complexity measure and its model for assembly lines have been developed in an earlier paper by the authors. According to the complexity models developed, assembly sequence determines the directions in which complexity flows. Thus proper assembly sequence planning can reduce complexity. However, due to the difficulty of handling the directions of complexity flows in optimization, a transformed network flow model is formulated and solved based on dynamic programming. Methodologies developed in this paper extend the previous work on modeling complexity, and provide solution strategies for assembly sequence planning to minimize complexity.     

面向多星任务规划问题的改进遗传算法

卫星数量的快速增加为管控卫星的工作增加了很大的难度,如何有效地进行任务规划,有效管理卫星资源,成为了卫星领域的一个重要问题.针对此问题,本文构建了多星任务规划的数学模型,将最大化任务收益作为优化目标.本文分析了问题的难点并提出了一种包含两种优化策略的改进遗传算法,包括全局优化和局部优化两部分.全局优化和局部优化根据种群改进情况进行自适应切换.通过两种优化方法的结合可以提升任务规划的效果.本文还提出了一种任务规划算法,用于为改进遗传算法得到的任务序列选择合适的任务执行时间.仿真实验证明本文提出的改进遗传算法可以很好地解决多星任务规划问题,与对比算法相比可以得到更优的规划结果.改进遗传算法有很好的工程应用前景.     

Two-handed assembly with immersive task planning in virtual reality

Assembly modelling is the process of capturing entities and activity information related to assembling and assembly. Currently, most CAD systems have been developed to ease the design of individual components, but are limited in their support for assembly designs and planning capability, which are crucial for reducing the cost and processing time in complex design, constraint analysis and assembly task planning. This paper presents a framework of a two-handed virtual assembly (VA) planner for assembly tasks, which coordinates two hands jointly for feature-based manipulation, assembly analysis and constraint-based task planning. Feature-based manipulation highlights the important assembling features (e.g. dynamic reference frames, moving arrow, mating features) to guide users for the ease of assembly and in an efficient and fluid manner. The users can freely navigate and move the mating pair along the collision-free path. The free motion of two-handed input in assembly is further restricted to the allowable motion guided by the constraints recognised on-line. The allowable motion in assembly is planned by the logic steps derived from the analysis of constraints and their translation in the progress of assembly. No preprocessing or predefined assembly sequence is necessary since the planning is produced in real-time upon the two-handed interactions. Mating features and constraints in databases are automatically updated after each assembly to simplify the planning process. The two-handed task planner has been developed and experimented for several assembly examples including a drill (12-parts) and a robot (17-parts). The system can be generally applied for the interactive task planning of assembly-type applications.     

A physically based approach with human–machine cooperation concept to generate assembly sequences

Assembly plan is considered one of the important stages to minimize the cost of manufacturer and to ensure the safety of assembly operation, the main problem of assembly sequence planning approach is how to reduce the deviation from the real manufacture conditions. In this paper, we have extensively investigated a novel approach to automatically generate the assembly sequences for industrial field, which is especially applied to other large-scale structures. A physically based assembly representation model includes not only the pre-determined basic assembly information, such as precedence relations between parts or subassemblies, geometric constraints, different assembly types, and also the dynamic real-time physical properties, such as the center position of gravity, the force strength of the part, et al. This representation model considered the influences on optimum sequences by assembly operations will be modified by the feedback from interactive virtual environment. Then, we select the safety, efficiency and complexity as the optimization objectives. A hybrid search approach may be used to find the optimum assembly sequence, which will be integrated into an interactive assembly virtual environment (IAVE). It means that the results of assembly interaction can be provided to update the assembly planning model as a feedback, by which the approach will take advantages of the immune memory for local optimum search. The user can adjust the assembly sequences with obvious good objective by interaction with IAVE to improve the performance of the search algorithm. We describe human–machine cooperation (HMC) method for ASP in this work, by which human also can play a pivotal role instead of pure soft-computing. A series of numerical experiments are done to validate the performance of the physically based approach (PBA) to generate assembly sequence, which shows the efficiency and the operability to guide the assembly work.     

Illumination setup planning for a hand-eye system based on an environmental model

In hand-eye systems for advanced robotic applications such as assembly, the degrees of freedom of the vision sensor should be increased and actively made use of to cope with unstable scene conditions. Particularly, in the case of using a simple vision sensor, an intelligent adaptation of the sensor is essential to compensate for its inability to adapt to a changing environment. This paper proposes a vision sensor setup planning system which operates based on environmental models and generates plans for using the sensor and its illumination assuming freedom of positioning for both. A typical vision task in which the edges of an object are measured to determine its position and orientation is assumed for the sensor setup planning. In this context, the system is able to generate plans for the camera and illumination position, and to select a set of edges best suited for determining the object's position. The system operates for stationary or moving objects by evaluating scene conditions such as edge length, contrast, and relative angles based on a model of the object and the task environment. Automatic vision sensor setup planning functions, as shown in this paper, will play an important role not only for autonomous robotic systems, but also for teleoperation systems in assisting advanced tasks.     

The development of an autonomous assembly robot

This paper presents various projects which are being developed at the Institute for Informatics at the Robotics Research Group. Several of these projects will be integrated to support the development of an autonomous assembly robot. With its two arms under sensor guidance, the robot will be capable of assembling a standard benchmark (workpieces). To achieve mobility, the robot will be equipped with a self-propelled platform. Several vision systems are employed in order to support the navigation of the robot and the assembly task. An AI-based system is being developed for assembly planning, implicit programming, route planning (obstacle avoidance), assembly monitoring, and error recovery.     

Fine motion strategy for skill-based manipulation

Generally, a manipulator task can be divided into several motion primitives called “skills.” Skill-based motion planning is an effective way to execute a complicated task. When planning an assembly process, a technique of fine motion planning such as the backprojection method in configuration space is often used. This paper describes fine motion planning using a skill library, which consists of a pattern of trajectories of skill motions in configuration space. This method gives the initial position and orientation from which the object can reach the goal in skill-based manipulation.     

Comparison of intelligent control planning algorithms for robot's part micro-assembly task

Two intelligent control (path or motion) planning algorithms, based on a neural network and a fuzzy set theory, related to a robotic quasi-static part micro-assembly task are introduced. The part micro-assembly considered in this paper consists in a mating a part with an assembly hole or a receptacle (target) without a jamming. These algorithms are then compared through the utilization of experimentally measured data as well as simulations and a set of criteria. An entropy function, which is a useful measure of the variability and the information in terms of uncertainty, is introduced to measure its overall performance of a task execution related to the part micro-assembly task. Fuzzy set theory is introduced to address the uncertainty associated with the part micro-assembly procedure. The degree of uncertainty associated with the part micro-assembly is used as an optimality criterion, e.g. minimum fuzzy entropy, for a specific task execution. It is shown that the machine organizer using a sensor system can intelligently determine an optimal control value, based on explicit performance criteria. The algorithms utilize knowledge processing functions such as machine reasoning, planning, inferencing, learning, and decision-making. The results show the effectiveness of the proposed approaches. The proposed techniques are applicable to a wide range of robotic tasks including motion planning, pick and place operations, and part mating with various shaped parts.     

Physics-based virtual reality for task learning and intelligent disassembly planning

Physics-based simulation is increasingly important in virtual manufacturing for product assembly and disassembly operations. This work explores potential benefits of physics-based modeling for automatic learning of assembly tasks and for intelligent disassembly planning in desktop virtual reality. The paper shows how realistic physical animation of manipulation tasks can be exploited for learning sequential constraints from user demonstrations. In particular, a method is proposed where information about physical interaction is used to discover task precedences and to reason about task similarities. A second contribution of the paper is the application of physics-based modeling to the problem of disassembly sequence planning. A novel approach is described to find all physically admissible subassemblies in which a set of rigid objects can be disassembled. Moreover, efficient strategies are presented aimed at reducing the computational time required for automatic disassembly planning. The proposed strategies take into account precedence relations arising from user assembly demonstrations as well as geometrical clustering. A motion planning technique has also been developed to generate non-destructive disassembly paths in a query-based approach. Experiments have been performed in an interactive virtual environment including a dataglove and motion tracker that allows realistic object manipulation and grasping.     

Architectural space planning using evolutionary computing approaches: a review

This paper presents various applications of evolutionary computing approach for architectural space planning problem. As such the problem of architectural space planning is NP-complete. Finding an optimal solution within a reasonable amount of time for these problems is impossible. However for architectural space planning problem we may not be even looking for an optimal but some feasible solution based on varied parameters. Many different computing approaches for space planning like procedural algorithms, heuristic search based methods, genetic algorithms, fuzzy logic, and artificial neural networks etc. have been developed and are being employed. In recent years evolutionary computation approaches have been applied to a wide variety of applications as it has the advantage of giving reasonably acceptable solution in a reasonable amount of time. There are also hybrid systems such as neural network and fuzzy logic which incorporates the features of evolutionary computing paradigm. The present paper aims to compare the various aspects and merits/demerits of each of these methods developed so far. Sixteen papers have been reviewed and compared on various parameters such as input features, output produced, set of constraints, scope of space coverage-single floor, multi-floor and urban spaces. Recent publications emphasized on energy aspect as well. The paper will help the better understanding of the Evolutionary computing perspective of solving architectural space planning problem. The findings of this paper provide useful insight into current developments and are beneficial for those who look for automating architectural space planning task within given design constraints.     

Intelligent optimization of component onsertion in multi-head concurrent operation PCBA machines

The placement or onsertion of surface mounted components is an essential stage in printed circuit board assembly (PCBA). A reduction in production time of placement through efficient process planning will significantly increase total yield of the whole line. Addressed in this paper is the task of achieving high yield through determination of an optimal placement sequence given the constraints of feeder arrangement and machine design. A knowledge-based component placement system (CPS) which incorporates optimization algorithms is presented for a sophisticated but popular multi-head concurrent assembly machine. CPS has proven, in comparison to the machine proprietary algorithm, to be more practical and effective. CPS, a hybrid, which uniquely couples mathematical algorithms with a knowledge base, is a powerful tool in process PCB assembly.     

基于De Bruijn图的De Novo序列组装软件性能分析

随着新一代测序技术的发展,一些新的全基因组组装算法应运而生,特别是针对第三代高通量测序仪产生的海量短序列的组装软件被不断开发出来,这些组装软件渐渐走向市场。但是,由于这些组装软件的适用性和其性能的差别,选择一款性能优良的组装工具或者开发并行高吞吐的组装工具成为了当前面临的一大难题。本文选取基于 De Bruijn 图算法开发的 4 款 De Novo 组装的软件（Velvet、SOAPdenovo、IDBA、ABySS）对 4 种物种的基因组的模拟数据进行测试,并从软件的算法、组装性能和组装质量 3 个方面分析这 4 个软件的性能,同时根据其算法特点推断影响这些软件性能的关键因素,并给出软件的使用建议以及开发并行序列组装工具来组装超大规模的基因数据应该注意的问题。     

Task-oriented motion planning for multi-arm robotic systems

In this paper a task-oriented motion planning approach for general cooperative multi-robot systems is proposed. In order to derive a meaningful task formulation, a taxonomy of cooperative multi-arm systems of industrial interest is devised. Then, a workpiece-oriented general formulation for cooperative tasks is proposed, where the user is asked to specify the motion of the system only at the workpiece level, while the motion of the single arms in the system is computed via kinematic transformations between the relevant coordinate frames. Based on this task formulation, an instructions set is derived to extend classical programming languages for industrial robots to general multi-robot systems. In order to test the approach, a software environment has been built, composed of an interpreter of the language and the motion planning software.     

Development of a virtual and physical work cell to assemble micro-devices

The term ‘micro-assembly’ is used to describe the assembly of micron-sized parts that are extremely small (in the order of 10⁻⁶ m). As manual assembly of micro-devices is extremely difficult and tedious, there is a need to design computer-controlled approaches to facilitate rapid assembly. In this context, the design of automated or semi-automated environments for micro-assembly applications becomes important. In this paper, the design of a micro-assembly cell is discussed along with the development of a virtual assembly environment to study micro-assembly problems and issues. A genetic algorithm-based assembly sequence generator is discussed which works in coordination with a 3D path planning approach. A physical micro-assembly cell has been created to aid in the assembly of such micro-devices. This physical cell is interfaced with a virtual reality (VR)-based assembly environment to assist in the micro-assembly activities and comprises of micro-positioners, a micro-gripper (for pick-and-place operations to complete specific micro-assembly tasks), and a camera (to provide guidance and feedback during and after assembly).     

Recent trends in flexible automated manufacturing

In recent years, an important change in developing and implementing manufacturing systems can be observed in all industrialized countries. Due to intense international competition and the growth of personnel costs, companies are forced to use systems with a higher level of automation. At the same time, an increasing number of product variation—caused by adapting the products to customer requirements—demand more flexibility of machine tools and manufacturing systems.Basic types of computer-controlled flexible automated manufacturing systems will be shown and characterized by their special ranges of application. A planning procedure is presented which includes selecting a suitable systems structure such as; transfer line or flexible manufacturing system or automated manufacturing cell, and for determinating every single machine tool within the system. Examples of several new computer-controlled manufacturing systems which have been planned by the above planning procedure are presented with special regard to the evaluation of the system's economic performance.Finally, some rules are given for measuring the economic performance of automated manufacturing or assembly systems including automation of the handling functions.     

An ontology-oriented knowledge methodology for process planning in additive layer manufacturing

The goal of this research is the generation of a novel knowledge with process-oriented ontology and the informal model. With regard to the proposed ontology, it establishes an improvement to related ontologies because it involves the demands of fabrication engineering and, specifically, the layer-upon-layer manufacturing planning process with various AM systems. Generally, task of AM planning indicates to make repeated and essential decisions which are always on the basis of the engineers’ knowledge and experience in additive manufacturing. Hence, it is a suitable field towards the execution of a knowledge-based engineering system. To represent the knowledge at an upper tier, the IDEF0 diagrams is introduced for identifying the sequence of tasks contained in the AM planning. They are a vital resources for defining the sequence of tasks and the messages flow. Afterward, these messages are analyzed thoroughly by applying schematic graphs, and then they are categorized into knowledge segments. Eventually, each knowledge segment is further divided into knowledge entities. At the same time, the relationships among them are also defined.Meanwhile, knowledge modeling involved generating an ontology of design feature which is utilized as a general information model in both computer-aided design and process planning, expression of fabrication criteria that depict the basis and properties for picking fabrication parameters. In a first method, the ontology has been examined utilizing an essential activity in AM planning: the task related to the confirmation of parameters over component quality. In this task, decisions have to be made in the orientation, slicing and the other process parameters. In this research, the differences between geometric and dimensional tolerance fabrication is considered in the generated methodology. The knowledge needed to aid all decisions is expressed utilizing the proposed ontology.     

Taxonomy for the Network and Service Management Research Field

Network and service management has established itself as a research field in the general area of computer networks. However, up to now, no appropriate organization of the field has been carried out in terms of a comprehensive list of terms and topics. In this paper, we introduce a taxonomy for network and service management. With such a taxonomy, it is possible to better understand the landscape of research as well as to reason about possible future challenges and opportunities. As such, in addition to the taxonomy itself, we also present an initial analysis of the field’s past, present, and future, based on the records of papers submitted and accepted in major conferences in the area, as well as a site survey performed through a questionnaire answered by experts from both industry and academia.     

Application of robots in assembly automation

The development of flexible assembly is closely related to the introduction of robots in assembly automation. If has long been recognized that automatic parts assembly by robots is one of the most delicate and most difficult tasks in industrial robotics. This task involves two control problems, trajectory planning for the whole automatic assembly process and reduction of the reaction forces appearing between the parts being assembled. This paper addresses both aspects of this control task. The strategical control level for the manipulation of robots and various approaches to trajectory planning tasks in assembly processes are discussed. A new approach to the determination of the strategical control level, including various models (geometric, kinematic and dynamic) for manipulation robots, is briefly described.The last and most delicate phase of the assembly process is parts mating, which is rather like inserting a peg in a hole. In order to reduce the reaction forces appearing between the parts being assembled, force feedback control is applied. The experimental results of the industrial robot insertion process with force feedback are also presented in the paper.     

Assembly features in modeling and planning

In recent years, features have been introduced in modeling and planning for manufacturing of parts. Such features combine geometric and functional information. Here it is shown that the feature concept is also useful in assembly modeling and planning. For modeling and planning of both single parts and assemblies, an integrated object-oriented product model is introduced. For specific assembly-related information, assembly features are used. Handling features contain information for handling components, connection features information on connections between components. A prototype modeling environment has been developed. The product model has been successfully verified within several analyses and planning modules, in particular stability analyses, grip planning, motion planning and assembly sequence planning. Altogether, feature-based product models for assembly can considerably help in both assembly modeling and planning, on the one hand by integrating single-part and assembly modeling, and on the other hand by integrating modeling and planning.     

Automatic grasp planning for multifingered robot hands

In this paper the development of a planning environment is described which was especially tailored for grasping and manipulating with multifinger robot hands. The research has been concerned with the programming and simulation system of the Karlsruhe dextrous hand, which has been in development for two years. The work presents the result of a geometric-mechanic approach to the object-handling problem with dextrous multifinger hands by selecting grasp points and searching grasp forces to perform desired assembly tasks. The knowledge representation for the sequence planning and command execution is based on object and task restrictions combined with routines for successive optimization and a constraint propagation algorithm.