Högskolan i Skövde

Manufacturing companies today need to maintain a high level of flexibility and adaptability to deal with uncertainties on dynamic shop floors, including e.g. cutting tool shortage, part supply interruption, urgent job insertion or delay, and machine unavailability. Such uncertainties are characteristic in component assembly operations. Addressing the problem, we propose a new method using function blocks to achieve much improved adaptability in assembly planning and robot control. In this paper, we propose to use event-driven function blocks for robotic assembly, aiming to plan trajectory and execute assembly tasks in real-time. It is envisioned that this approach will achieve better adaptability if applied to real-world applications.

Today, the dynamic market requires manufacturing firms to possess high degree of adaptability and flexibility to deal with shop-floor uncertainties. Specifically, targeting SMEs active in the machining and metal cutting sector who normally deal with complex and intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Web-DPP elaborates a two-layer distributed adaptive process planning system based on function-block technology. Function-block enabled machine controllers are one of the elements of this system. In addition, intensive reasoning based on the features data of the products models, machining knowledge, and resource data is needed to be performed inside the function blocks in machine controller side. This paper reports the current state of design and implementation of a knowledge-based operation planning module using a rule-engine embedded in machining feature function blocks, and also the design and implementation of a common interface (for CNC milling machine controller and its specific implementation for a specific commercial controller) embedded in the machining feature function blocks for controlling the machine. The developed prototype is validated through a case-study.

In attempt to have a flexible manufacturing environment with adaptive control systems, several researchers tend to integrate vision systems into the industrial systems to achieve that objective; the majority of the research works that have been done in this perspective tend to keep this kind of integration fully automated. Along the same direction, this paper presents an approach for integrating Robotic Sketching and Path Planning with Image Processing, and it introduces at the same time the ability for operators to remotely control and monitor the processing stages. It has been accomplished using network based architecture consisting of a vision system together with a server, a client and an ABB industrial robot. The aims of this paper are: (1) to provide an example that illustrates the benefit of interfacing the image processing techniques with the industrial shop floor system, and (2) to develop a web based system that allows an operator to remotely monitor and control the stages of the application using Java based applet. Further analyses have been done for the processing times of the application; this helped us to address the problem that consumed the largest proportion of the processing time. The work that has been done in this research provides additional supervision ability for the integrated system, and it demonstrates some of the challenges and the obstacles that may face this kind of integration.

The dynamic market today requires manufacturing companies to possess high degree of adaptability and flexibility in order to deal with shop-floor uncertainties. Such uncertainties as missing tools, part shortage, job delay, rush-order and unavailability of resources, etc. happen more often in assembly operations. Targeting this problem, this research proposes a function block enabled approach to achieving adaptability and flexibility in assembly planning and control. In particular, this paper presents our latest development using a robotic mini assembly cell for testing and validation of a function block enabled system capable of assembly and robot trajectory planning and control. It is expected that a better adaptability can be achieved by this approach.

In order to improve the production efficiency while facing today’s manufacturing uncertainty, responsive and adaptive capabilities for rapid production changes are essential. This paper presents how dynamic control and real-time monitoring (embedded in a web-based Wise-ShopFloor framework) can integrate virtual models with real shop floors. Wise-ShopFloor (Web-based integrated sensor-driven e-ShopFloor)uses Java technologies (e.g., Java Servlet and Java3D) for implementing the system. It allows the operators, both remote and on-site, to monitor and control machines, devices and operations on a shop floor, based on run-time information from the connected machines, devices and their sensors. Two case studies are presented to demonstrate the approach towards web-based adaptive manufacturing. The first demonstrating how OPC-technology is used to improve the monitoring and control capabilities of the production and the second one focusing  on remote control of a robot eliminating the need of motion planning and tedious robot programming.

This paper presents an integrated approach for remote real-time monitoring of manufacturing operations. It is enabled by using virtual 3D models driven by real sensor data. The objectives of this research are twofold: (1) to significantly reduce network traffic for real-time monitoring over the Internet: and (2) to increase the controllability of manufacturing systems from anywhere in a decentralised environment. Particularly, this paper covers the principle of the approach, system architecture, prototype implementation, and a case study of remote control of a robotic assembly cell. Compared with camera-based monitoring systems, our approach only consumes less than 1% of its network bandwidth, feasible and practical as a web-based portable solution. (C) 2011 CIRP.

Many problems in the lifecycle of Product and Production Development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described.

Many problems in the lifecycle of product and production development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and virtual manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described. (C) 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

Performing assembly planning to find a valid hierarchical assembling structure of a product (i.e. Manufacturing Bill of Materials or MBOM) based on the constraints and necessities inferred from or declared by different sources is potentially complicated. On the other hand, Engineering Changes (EC) may drastically affect the constraints and necessities which the planning of an MBOM was based on. Managing ECs to evaluate and propagate their effects on the upstream data used in assembly planning and downstream activities and information is crucial but problematic. Often it is possible to define a set of rules for the constraints and necessities of assembly planning and find solutions or check validity of solutions based on the rule-set. This paper proposes a rule-based assembly planning method and introduces the concepts and standard notations on how structured rule-sets can be derived from descriptive rules and then used in an algorithm for generating or validating MBOMs. The method was partially automated and successfully employed along with a commercial Virtual Manufacturing package integrated with an in-house developed GA-based sequence optimizer and applied to the sequence optimization in minimizing the cycle time of the robotic spot welding operations for a sheet-metal assembly found in automotive industry. (C) 2011 Elsevier Ltd. All rights reserved.