Simulation of a generic flexible assembly system

Flexible Assembly Systems - Hardware Components and Features: Basic components of a FAS.- Classification of flexible assembly systems.- Examples of industrial installations.- Issues in Design, Planning and Scheduling of Flexible Assembly: FAS design issues.- Network design for material flow systems.- Design for assembly.- Assembly planning.- Planning and scheduling.- Loading and Routing Decisions in Flexible Assembly Systems: Description of a flexible assembly system.- Optimization of station workloads and product movements.- Design and balancing of flexible assembly lines.- Numerical examples.- Simultaneous loading and routing.- Sequential loading and routing.- Loading and Routing Decisions with Assembly Plan Selection: Simultaneous loading, routing and assembly plan selection in a general flexible assembly system.- Simultaneous loading, routing and assembly plan selection in a flexible assembly line.- Loading and Scheduling in Flexible Assembly Cells: Loading and scheduling in a robot assembly cell.- Loading and sequencing in printed circuit board assembly.- Production Scheduling in Flexible Assembly Lines: Flexible assembly line with limited intermediate buffers.- Flexible assembly line with no in-process buffers.- Global lower bounds for flexible flow lines with unlimited buffers.- Just-in-time scheduling of flexible assembly lines.- Multilevel scheduling of flexible assembly lines with limited intermediate buffers.- Machine and Vehicle Scheduling in Flexible Assembly Systems: Dispatching scheduling.- Machine and vehicle scheduling - a multi-level approach.- Machine and vehicle scheduling - a single-level approach.

Recently a major trend in flexible and precision assembly automation, and in automation in general, has been in robots that can safely work next to people. Increasingly, as part of collaborative automation, such robots are also designed to collaborate as teams with other robots. These intelligent machines are called cobots, or collaborative robots, and are reducing the cost and time to install robots in many applications. Flexible and precision assembly refers to an assembly system that can build multiple similar products with little or no reconfiguration of the assembly system. It can serve as a model for some of the emerging applications in flexible and precision automation. Precision assembly implies assembly with precise motions and operations. Recently, machine learning interacting with the robots’ sensors enables robots to assemble parts and components with precision that exceeds their own motion precision. A truly flexible assembly system would enable precision assembly, include flexible part feeding, grasping, and fixturing, as well as a variety of mating and fastening processes that can be quickly added or deleted without costly engineering. There is a limited science base for how to design flexible assembly systems in a manner that will yield predictable and reliable throughputs. The emergence of geometric modeling systems (as part of CAD) has enabled work in geometric reasoning in the past few years. Geometric models have been applied in areas such as machine vision for object recognition, design, and throughput analysis of flexible part feeders, dynamic simulation of assembly stations and assembly lines. Still lacking are useful techniques for automatic model generation, planning, error representation, error prevention (avoidance), and error recovery. Future software architectures for flexible and precision automation should include geometric modeling and reasoning capabilities to support autonomous, sensor-driven systems.

As manufacturing trends shift towards customized production, the demand for agile automation systems capable of efficient adaptation to rapidly changing task requirements is rising. This work presents a flexible robotic assembly system that combines CAD based component localization, compliance control, and a multi-modal gripper to enable robust and efficient programming of complex tasks. The process can be easily configured for novel assemblies through a dedicated Graphical User Interface (GUI), which facilitates component identification and task sequencing. Component poses are extracted from 3D CAD models in reference to the assembly origin, while the active compliance scheme compensates for minor positioning errors. The gripper incorporates a parallel jaw element, a rotating module, and an electromagnet to minimize retooling delays. The first iteration of the proposed system placed first in the manufacturing track of the Robotic Grasping and Manipulation Competition of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), experimentally validating its efficiency.

Components of the Design Process of Flexible and Reconfigurable Assembly Systems

The paper presents integer programming formulations and an approximative lexicographic approach for a bicriterion loading and routing problem in a flexible assembly system. The problem objective is to determine an assignment of tasks to assembly stations for a set of products so as to balance station workloads and minimize total interstation transfer time. In the approach proposed, first the station workloads are balanced using a linear relaxation-based heuristic and then assembly routes are selected based on a network flow model. An illustrative example is provided and some results of computational experiments are reported.

To date, holonic manufacturing system (HMS), one of the novel concepts to meet the increasing globalization and customization of the manufacturing processes, has been conceptually constructed, and prototyping systems, holonic fixturing station (HOLOFIX), holonic autonomous guided vehicles (H-AGVs) etc. were developed with enhanced performances in their specific processes. This work presented an object oriented technology (OOT)-supported migration approach to holonic robot assembly cell. Based on the analysis of activities in the flexible assembly cell, an architecture of workstation for holonic robot assembly cell was proposed. The holonic robot workstation was established by incorporating a control computer that performs production planning, shop floor control and local operations into each of robot systems in the flexible assembly cell, workstations of this kind functions as the building blocks of holonic robot assembly cell. The holonic robot assembly cell employs a dynamic holarchy evolution mechanism to carry out assembly tasks. The entire implementation was conducted on the flexible assembly system in PMA/Leuven.

One of the major challenges in commercializable micro-nano systems development is the high cost and turnaround that are incurred through multiple product-optimization iterations and expensive fabrication processes for specific systems. Development of complex and heterogeneous micro-nano systems, that are only possible through assembly and not by conventional surface machining approaches, are further impeded by lack of standard design rules and off-the-shelf robotic manipulation systems. Dedicated hardware and system specific component designs, although possible, are not commercially viable for addressing the wide range of opportunities that exists in the prevailing micro-nano domain. In this paper, we present an alternative and holistic top-down approach for micro-nano manufacturing using modular part designs and flexible assembly systems. We incorporate, seamlessly, multiple novel algorithms related to microrobotics and scaling of physics, obtained both analytically as well as experimentally; in order to predict, track and control the uncertainty propagation in a typical manufacturing process, in micro-nano scale, throughout production steps including design, machining, setup, assembly, testing etc. We demonstrate, through multiple examples, the implementation of the proposed framework in micro-nano scale manufacturing.

Flexible Assembly Systems through Workplace-Sharing and Time-Sharing Human-Machine Cooperation (PISA)

Global competition and the rapid pace of technological change now require the almost continual introduction of product upgrades by any manufacturer. Thus, such a manufacturer is likely to market older and newer versions of a product simultaneously, not to mention niche-specific editions of any product upgrade. An increasingly successful response to this product proliferation is the implementation of flexible assembly systems. In the context of a flexible assembly system (FAS), the ability to estimate the impact of various product and process options on the maximal level of system output becomes crucial to managing the ever-changing product mix. This paper presents a tool for such impact estimation that can facilitate concurrent development and engineering. Experience with an actual FAS is the basis for the reported results. The tool is a specialized combination of discreteevent computer simulation, experimental design, and regression analysis. Application of the tool assumes FAS use with a cellular manufacturing philosophy. Thus, uncluttered process flow for a family of products in the sense of group technology places the focus on potential bottlenecks. The new tool here models the impact of process and product options on bottleneck and, hence, FAS behavior.

Advantages of Sub-Batch Principle in Flexible Automatic Assembly as Used in the IVF-KTH Concept Mark II

Optimal selection and control strategies for a flexible manufacturing and assembly system

An aggregate scheduling problem for a flexible manufacturing system which consists of a machining and an assembly subsystem is presented. The aggregate schedule developed is used as an input to a real-time scheduling problem discussed previously by the author (Proc. 2nd ORSA/TIMS Conf. on Flexible Manuf. Syst: Oper. Res. Methods and Appl., Elsevier NY, 1986, pp.521-32). Although features of the flexible manufacturing environment are not explicit at the aggregate scheduling level, they are incorporated at the real-time scheduling level. The single-product and N-product scheduling problems are considered. To solve the problems two optimal scheduling algorithms are developed. Each algorithm is illustrated with a numerical example. The results are also applicable to the single-batch and N-batch scheduling problems.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The successful implementation of a Flexible Manufacturing/Assembly System can be an effective means of reducing labor, resources and work-in-process inventory. It can increase equipment utilizations, improve quality and result in increased throughput. Simulation is an effective tool for analyzing critical system components and their inter-relationships; consequently, ensuring systems design meets throughput requirements at reduced costs. This paper presents an approach to the design, specification and implementation of a Flexible Assembly System (FAS) using simulation. It presents a practical approach for designing manufacturing systems involving uncertainties. Two simulation models are discussed:(1) a GPSS/H model and(2) a PCMODEL model.The GPSS/H model was used during the early FAS design and specification stage. The PCMODEL model was used to sell the proposed FAS configuration to management. The FAS has been successfully implemented.

AI AND COMPLEX SYSTEMS TECHNIQUES IN MANUFACTURING MANAGEMENT AND CONTROL

This paper proposes and analyzes an efficient robot task sequence for a flexible assembly system that consists of multiple 3D printers, post-processing, assembly, inspection machines, and a material handling robot. The flexible assembly system, which has been built in many large cities in Korea, has been designed to fabricate customized products for start-ups or individuals. We consider cyclic scheduling of the system in which the robot repeats a certain sequence to produce identical products. We propose a robot task sequence to minimize the cycle time. The system behavior with the proposed robot task sequence is modeled with a timed event graph (TEG), and the optimality of the sequence is proved by analyzing the circuits in the TEG. The results are extended for producing multiple types of products simultaneously.