Assembly 4.0: Wheel Hub Nut Assembly Using a Cobot

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.

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.

Components of the Design Process of Flexible and Reconfigurable Assembly Systems

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

During the early 1980s, the concept of a flexible assembly machine was first suggested by Hounsfield (1983). Following this, a variety of research projects have been conducted in an attempt to develop a flexible assembly system that is functional and economically viable. The most significant contribution has been made by the EURICA EU 321 - FAMOS - INFACT* project. However, despite the developments made during these projects, no industrial based system exists today. This paper presents a simulation model of a novel concept for a multi-station flexible automatic assembly machine, and examines the application of a rule based control strategy for the control of a materials handling system used in such a system. * http://www.3.eureka.be/home/

Following the success of flexible manufacturing systems (FMSs), their counterpart, flexible assembly systems (FASs), have been developed to automate factories further. As in a FMS, the cellular approach is considered as the most feasible and flexible configuration for a FAS by researchers. Because of the differences between manufacturing and assembly operations, the logic of cell formation between a FMS a FAS is not the same. This paper discusses the similarities and differences between FMSs and FASs, and assembly cell design problems. Since the time for assembly operation is usually relatively short, the transfer time is thus very crucial for the performance of assembly systems. Therefore a good assembly cell should be constructed in a way that the flows of products within this cell are mostly in sequence. More in-sequence flows usually have the advantages of smaller flow distance, easier material-handling problems and more efficient production. In order to achieve these advantages, we propose a...

A significant part of the activities in a manufacturing system involve assembly tasks. Nowadays, these tasks are object of automation due to the market increasing demand for quality, productivity and variety of the products. Consequently, the automation of assembly systems should consider flexibility to face product diversification, functionalities, delivery times, and volumes involved. However, these systems are vulnerable to faults due to the characteristic of their mechanism and the complex interaction among their control devices. In this context, the present work is focused on the modeling design of Flexible Assembly Systems control, including the occurrence of faults. The proposed method structures a sequence of steps for the models construction of assembly processes and their fault detection, based on the theory of Discrete Events Systems and Petri net. This work use in special, Production Flow Schema/Mark Flow Graph (PFS/MFG) technique to describe and model the Flexible Assembly Systems control through a rational and systematic procedure, as well as, the processes data record based on quantitative techniques for fault detection. This approach is applied to a Flexible Assembly Systems installed and in operation to compare the effectiveness of the developed procedure.

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>

An integrated system of master and fine scheduling of a flexible manufacturing (FMS) and assembly system (FAS) is discussed in this presentation.

In this paper, a flexible robotic assembly system with decentralized architecture is presented. The system is designed to achieve high reconfigurability so that it can adapt to changes in manufacturing environment; a new robot can be easily installed to the system and execute assembly tasks immediately, together with other devices. For easier reconfiguration, a semi-automated calibration method for positions of newly installed robots is integrated into the system. Our implementation of the assembly system consists of conventional manipulators and a belt conveyor. In the experiment, a new mobile manipulator was installed successfully and performed an assembly operation jointly with other existing manipulators.

Modular production system concept for a water tap assembly

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.

In order to complete the robot axle hole assembly task in an unstructured environment, an adaptive impedance control algorithm based on joint space force and position double feedback is proposed, and the assembly process adjustment strategy is designed to complete the assembly task. By installing a torque sensor on the joint of the six-axis cooperative robot, the control model of joint force position with double feedback is formed. By combining the model reference adaptive control (MRAC), operational force planning, and operational space motion planning, an assembly system based on joint space flexibility control is finally designed. According to the task of axle hole assembly, the geometric constraint analysis and force analysis are carried out in the axle hole assembly process, and the corresponding adjustment strategy is designed. The assembly experiments were carried out for holes with different gaps, and the pose parameters, contact force, and control adaptability parameters during assembly were analyzed experimentally. The experimental results show that the flexible assembly system can complete the shaft hole assembly well, and the assembly torque is controlled in a small range, which meets the assembly requirements.

This paper describes the development and early use of a test bed for Just‐In‐Time GIT) control of Flexible Assembly Systems (FAS). JIT has, up to now, been used in repetitive manufacturing systems. However, increasingly, companies involved in batch production who frequently use Materials Requirements Planning (MRP) approaches, are seeking to achieve the benefits of JIT, and to use Kanban type control at the operational level. The test bed simulation can be configured by the user to model a range of assembly systems each of which can, within limits, be configured by the experimenter. It is built using the SLAM II simulation package. Kanban cards are modelled as resources, as are the individual assembly stations and the transportation devices which carry work between the assembly stations. The test bed can be used to experiment with batch sizes, set‐up times, assembly station breakdowns, various Kanban sequences, varying purchasing lead times, etc. It allows experimentation with the application of the Kanban system to manufacturing systems which are not purely repetitive in nature and more closely resemble batch manufacturing 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.