On the Integration of Skilled Robot Motions for Productivity in Manufacturing

Robots used in manufacturing today are tailored to their tasks by system integration based on expert knowledge concerning both production and machine control. For upcoming new generations of even more flexible robot solutions, in applications such as dexterous assembly, the robot setup and programming gets even more challenging. Reuse of solutions in terms of parameters, controls, process tuning, and of software modules in general then gets increasingly important. There has been valuable progress within reuse of automation solutions when machines comply with standards and behave according to nominal models. However, more flexible robots with sensor-based manipulation skills and congnitive functions for human inteaction are far too complex to manage, and solutions are rarely reusable since knowledge is either implicit in imperative software or not captured in machine readable form. We propose techniques that build on existing knowledge by converting structured data into an RDF-based knowledge base. By enhancements of industrial control systems and available engineering tools, such knowledge can be gradually extended as part of the interaction during the definition of the robot task

The Analysis of design and manufacturing tasks using haptic and immersive VR - Some case studies

The use of virtual reality in interactive design and manufacture has been researched extensively but the practical application of this technology in industry is still very much in its infancy. This is surprising as one would have expected that, after some 30 years of research commercial applications of interactive design or manufacturing planning and analysis would be widespread throughout the product design domain. One of the major but less well known advantages of VR technology is that logging the user gives a great deal of rich data which can be used to automatically generate designs or manufacturing instructions, analyse design and manufacturing tasks, map engineering processes and, tentatively, acquire expert knowledge. The authors feel that the benefits of VR in these areas have not been fully disseminated to the wider industrial community and - with the advent of cheaper PC-based VR solutions - perhaps a wider appreciation of the capabilities of this type of technology may encourage companies to adopt VR solutions for some of their product design processes. With this in mind, this paper will describe in detail applications of haptics in assembly demonstrating how user task logging can lead to the analysis of design and manufacturing tasks at a level of detail not previously possible as well as giving usable engineering outputs. The haptic 3D VR study involves the use of a Phantom and 3D system to analyse and compare this technology against real-world user performance. This work demonstrates that the detailed logging of tasks in a virtual environment gives considerable potential for understanding how virtual tasks can be mapped onto their real world equivalent as well as showing how haptic process plans can be generated in a similar manner to the conduit design and assembly planning HMD VR tool reported in PART A. The paper concludes with a view as to how the authors feel that the use of VR systems in product design and manufacturing should evolve in order to enable the industrial adoption of this technology in the future

Knowledge-based systems and engineering software

The work described was carried out as part of a collaborative Alvey software engineering project (project number SE057). The project collaborators were the Inter-Disciplinary Higher Degrees Scheme of the University of Aston in Birmingham, BIS Applied Systems Ltd. (BIS) and the British Steel Corporation. The aim of the project was to investigate the potential application of knowledge-based systems (KBSs) to the design of commercial data processing (DP) systems. The work was primarily concerned with BIS's Structured Systems Design (SSD) methodology for DP systems development and how users of this methodology could be supported using KBS tools. The problems encountered by users of SSD are discussed and potential forms of computer-based support for inexpert designers are identified. The architecture for a support environment for SSD is proposed based on the integration of KBS and non-KBS tools for individual design tasks within SSD - The Intellipse system. The Intellipse system has two modes of operation - Advisor and Designer. The design, implementation and user-evaluation of Advisor are discussed. The results of a Designer feasibility study, the aim of which was to analyse major design tasks in SSD to assess their suitability for KBS support, are reported. The potential role of KBS tools in the domain of database design is discussed. The project involved extensive knowledge engineering sessions with expert DP systems designers. Some practical lessons in relation to KBS development are derived from this experience. The nature of the expertise possessed by expert designers is discussed. The need for operational KBSs to be built to the same standards as other commercial and industrial software is identified. A comparison between current KBS and conventional DP systems development is made. On the basis of this analysis, a structured development method for KBSs in proposed - the POLITE model. Some initial results of applying this method to KBS development are discussed. Several areas for further research and development are identified

Java based expert system for selection of natural fibre composite materials

Many research papers are published in the field of materials selection for manufacturing process and design of polymer composite materials. However, least consideration has been given for material selection of natural fibre composites. Intensive research carried out to use natural fibres as alternative materials for petrochemical based synthetic materials to enforce green technology in manufacturing engineering. There are several algorithm and methods are being proposed by various researchers in this field. Computer oriented materials selection and knowledge-based expert systems are the prevailing approach in materials selection. In this paper, we develop a technology for the materials selection system using Java based expert system. The weighted-range method (WRM) was implemented to identify the range value and to scrutinise the candidate materials. The expert system performance tested with automotive component as case study with high, medium and low precision criteria and the result sets generated by the expert system comply with industrial benchmark

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

A Knowledge Transfer Platform for Fault Diagnosis of Industrial Gas Turbines

The aim of this paper is to introduce the bases of an intelligent fault diagnostic platform, which assists in detecting mechanical failures of Industrial Gas Turbines (IGTs). This comprises an integration of an expert system and its complementary signal processing techniques. The essential characteristic here is not to exclude humans (experts) from the diagnostic process, but rather to transfer their knowledge and experience to a computerized platform. The automated process executed by the computerized platform is to ensure the scalability and consistency in fault diagnosis; while the humans are required to corroborate the transparency and liability of the outcomes. In this paper, a Knowledge Transfer Platform (KTP) is proposed for fault diagnosis of industrial systems. It is then designed and tested for combustion fault diagnosis using field data of IGTs. The preliminary results have revealed the feasibility and efficacy of the proposed scheme, which has the potential to be further extended to a large industrial scale and to different engineering diagnostic applications

The Feasibility of Using Expert Systems in the Management of Human Resources

The purpose of this paper is to introduce a decision aid that is being used increasingly in the business world, the expert system, and to begin to examine its potential for human resource management. First, the expert system technology is reviewed, with a special emphasis on the players, those involved in developing and using the system, and the parts, the three main components of a system. This is followed by an analysis of the costs and benefits and the advantages and disadvantages that have been ascribed to expert systems. We conclude this initial research endeavor by presenting some preliminary findings which suggest that employees are willing to cooperate with expert systems, even those that require personal information, and that they see some benefits to using expert systems as decision aids

Introduction of an Assistance System to Support Domain Experts in Programming Low-code to Leverage Industry 5.0

The rapid technological leaps of Industry 4.0 increase the pressure and demands on humans working in automation, which is one of the main motivators of Industry 5.0. In particular, automation software development for mechatronic systems becomes increasingly challenging, as both domain knowledge and programming skills are required for high-quality, maintainable software. Especially for small companies from automation and robotics without dedicated software engineering departments, domain-specific low-code platforms become indispensable that enable domain experts to develop code intuitively using visual programming languages, e.g., for tasks such as retrofitting mobile machines. However, for extensive functionalities, visual programs may become overwhelming due to the scaling-up problem. In addition, the ever-shortening time-to-market increases the time pressure on programmers. Thus, an assistance system concept is introduced that can be implemented by low-code platform suppliers based on combining data mining and static code analysis. Domain experts are supported in developing low-code by targeted recommendations, metric-based complexity measurement, and reducing complexity by encapsulating functionalities. The concept is implemented for the industrial low-code platform HAWE eDesign to program hydraulic components in mobile machines, and its benefits are confirmed in a user study and an industrial expert workshop.Comment: 8 pages, https://ieeexplore.ieee.org/abstract/document/983945

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Providing value to a business using a lightweight design system to support knowledge reuse by designers

This paper describes an alternative approach to knowledge based systems in engineering than traditional geometry or explicit knowledge focused systems. Past systems have supported product optimisation rather than creative solutions and provide little benefit to businesses for bespoke and low volume products or products which do not benefit from optimisation. The approach here addresses this by supporting the creativity of designers through codified tacit knowledge and encouraging knowledge reuse for bespoke product development, in particular for small to medium sized enterprises. The implementation and evaluation of the approach is described within a company producing bespoke fixtures and tooling in shorter than average lead times. The active support of knowledge management in the company is intended to add value to the business by further reducing the lead times of the designs and creating a positive impact to business processes. The evaluation demonstrates a viable alternative framework to the traditional management of knowledge in engineering, which could be implemented by other small to medium enterprises