Computer integrated fixture design system

Fixtures are used to locate, hold and support workpieces in manufacturing operations such as machining, inspection, and assembly. Designing and fabricating fixtures can take up to 10-20% of the total cost of a manufacturing system. Fixture planning is a complex activity restricted by the extreme diversity of workpiece, product batch size, product geometry, part accessibility, and working force. Computer-Aided Fixture Planning (CAFP) has been used to improve the fixture design for over 20 years. CAFP contributes to the reduction of lead-time and human interaction in fixture planning. It helps verification of the fixture quality and integration of fixture design with CAD/CAM systems. This paper summarizes constraints of fixture planning and four phases of CAFP. Various approaches to CAFP are surveyed. Application systems of CAFP including some recent patents are reviewed. The paper concludes with the research trend of CAFP. The global competition and customer demand change lead to greater product variety, smaller product batch size, shorter production time and higher product quality. Industrial organizations have to pursue flexibility and automation in manufacturing systems to remain competitive and profitable. Flexible Manufacturing System (FMS) developed in the past decades is to meet such challenge. FMS usually consists of one or more CNC machines which are capable of machining a variety of workpieces. With the development of Computer- Aided Design and Computer-Aided Manufacturing (CAD/ CAM) technology, product design and machining program- ming have been greatly computerized. However, one of the difficulties in FMS is the fixture design for locating and securing a workpiece during manufacturing operations. Fixture planning is time-consuming as it is customized for workpieces. Computer-aided fixture planning (CAFP) aims to reduce the lead-time and human interaction in fixture planning. It can verify fixture quality to integrate fixture design with CAD/CAM systems by automating the reasoning process. The integration of CAFP with CAD/CAM has greatly reduced the production lead-time and cost for an overall optimal solution in product design and manufacturing (1). Fixtures are used to locate, hold and support workpieces in manufacturing operations such as machining, inspection, and assembly. Fixture design and manufacturing is costly due to the tight tolerance and restricted machining opera- tions. Designing and fabricating fixtures can take up to 10- 20% of the total cost of a manufacturing system. Dedicated fixtures are mostly applied in mass production to gain high efficiency. For smaller batch size, the fixture flexibility becomes more important than efficiency due to the workpiece variety and machining requirements. Flexible and

Configure-to-Order (CTO) assembly systems are becoming pivotal in meeting the rising demand for mass customization. However, enabling rapid and cost-effective system reconfiguration remains a major challenge in manufacturing. Despite the flexibility of general-purpose machines, fixture design introduces significant bottlenecks, often requiring extensive manual effort to access, organize, and interpret fragmented or incomplete data. This leads to inefficient design pipelines that can compromise product functionality and result in costly redesign iterations, even when using advanced Computer-Aided Fixture Design (CAFD) tools. Although the Model-Based Definition (MBD) paradigm offers a promising response to these information-related challenges, its adoption within the CAFD domain remains limited. This work aims to support the broader adoption of MBD in this field through a multi-level contribution. First, a structured literature review identifies the essential semantic information required in an MBD dataset tailored to CAFD. Second, this content is structured in a machine-readable form using the ISO standard STEP AP242. Third, an MBD-driven CAFD framework is proposed. Finally, a proof-of-concept CAFD tool is developed by integrating established methodologies with commercial software to automate non-value-added tasks, such as configuring Computer-Aided Technologies (CAx). The results demonstrate the potential of this approach to streamline CAFD processes and establish a fully connected digital thread.

Advances in the technology of flexible manufacturing systems, and the introduction of concurrent engineering of product and process design have propounded the need for computer aided fixture design systems. Computer aided process planning is the interface between design and manufacturing and has a key role in achieving integration between the various modules in an FMS environment. Fixture design is inseparable from process planning, and hence to be of practical use any CAPP system must include fixture design. The past few years have seen great advances in automated fixture design systems and the tools used to achieve them. With the exception of fixture design for a limited range of products with close family similarity, fully automated design of practical fixtures is not yet achievable. The advances described in this book have widened the scope of application of computer aided fixture design and provide enhanced links with other product and process design activities.

Chapter 3 - Computer-aided fixture design

Network technology plays a vital role in integrating manufacturing facilities and controlling production information flows. A computer-integrated manufacturing (CIM) system with different production characteristics, e.g., production throughput rate and the amount of process infonnation, should be facilitated with a network protocol that meets the individual CIM system's requirements. PEO-NET, a Production-Efficiency-Oriented Network Evaluation Tool, is developed in this paper which adopts network efficiency (Esys), an improved practical perfonnance evaluation index, as the decision criteria while determining the installation suitability of the tentative network protocol. In order to achieve greater portability and flexibility, PEO-NET is designed with three replaceable modules: 1) the CIM system configuration module for defining the configuration of a CIM system as well as its production requirements, 2) the industrial network protocol simulation module for predicting the production communication behavior under different network protocols, and 3) the network perfonnance analysis module for generating the network efficiency significance decision table. Simulations are also perfonned to demonstrate how PEO-NET is facilitated as a decision support tool for selecting a feasible network protocol for both job shop and flow shop production environment with two major LAN (Local Area Network) protocols: Carrier Sense Multiple Access with Collision Detection (CSMA/CD) and Token Passing Bus, respectively.

A review and analysis of current computer-aided fixture design approaches

The modeling of flexible manufacturing systems (FMS) under uncertainty and evaluation of a rule base for online scheduling is considered. To represent uncertain events in FMS, such as failure of machine tools, repair time and processing time, apply continuous-time and discrete-time stochastic Petri nets with hierarchical structure to constructing the FMS model. To obtain an efficient schedule of FMS with on-line real-time basis, the authors construct a rule base and evaluate the performance of the rule base using the FMS simulation system. >

Technologies such as Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT) increasingly disrupt traditional manufacturing and production systems. However, there is a scarcity of empirical studies synthesising and evaluating the impact of disruptive technologies on existing manufacturing systems. This study examines the impact of AGVs applying IoT on Flexible Manufacturing Systems (FMS) through a case study demonstrating the integration of AGVs with IoT in a manufacturing company. As a concept, FMS was conceived decades ago; this study uses socio-technical systems theory to elaborate the concept of FMS into the current context. Key themes uncovered from the literature review include (i) AGVs in warehouse systems, (ii) AGV scheduling and routing, (iii) Human-machine interface, and (iv) integrating and controlling AGVs/IoT. The case study demonstrates how AGVs can create smart, flexible manufacturing systems by taking the following steps: (a) problem identification, (b) performance measurement, (c) designing the proposed solution, (d) evaluate IoT systems, (e) implementation of the new solution, and (f) future improvements. The study concludes with specific recommendations to implement Industry 4.0 in manufacturing companies.

Design of Software System Based on Axiomatic Design

Fixture design has traditionally been regarded as a manual process due to extensive requirements of heuristic knowledge and skilled craftsmanship. There are many mathematical and scientific formulae which can be used to calculate cutting forces, deflection of structural members, tolerance analysis of locating datum, etc. However many of the good fixture design features such as ease of loading/unloading, safety considerations, ingenuity in securing the workpieces, etc come from the experience and skill of the designers. Due to the extensive requirements of heuristic knowledge and craftsmanship, the automation of fixture design has not been considered possible in the past. Recent developments in artificial intelligence techniques and, in particular, knowledge representation have provided great opportunities in automating this field.

The current article introduces a solution to provide a decision support system (DSS) by combining artificial neural network (ANN) and fuzzy analytic network process (FANP) in order to select the flexible manufacturing system (FMS). In this context, a case study in factory of Tashgaz Company, specialists and MATLAB software are used. Given that today’s manufacturing systems are moving toward FMSs, and most of the similar pieces of research have used flexible manufacturing cells and AHP in definite mode, fuzzy numbers were used to compare criteria such as manufacturing rate, manufacturing accuracy, energy consumption, etc. for selecting manufacturing system, and a three-layered ANN was also used to create an expansion motor, and then, FANP was used for systemic selection instead of cell selection. And, the proposed model was implemented in a case study to explain more.

In this study, a new and simple alternate routing heuristics, which would be superior to the conventional routing strategies in terms of various system performance measures and easier to apply practically, was presented. Because of the high investment costs of FMSs, it is also definitely worth choosing the best operating policy and system configuration by analyzing the system model, and adapting to changes over time. In future research, the heuristic rule base will be extended to include other supplementary constraints such as dynamic tool allocation and sequence dependent setup times. For practical implementation of the proposed decision support system, additional research in the area of human interfaces could be useful to develop more user friendly system which automatically constructs simulation model of the system from the knowledge base of a production system.

Summary form only given as follows. As manufacturers face a more competitive environment, they are forced to satisfy needs for productivity and flexibility simultaneously. To satisfy these needs and remain competitive, many manufacturers are upgrading their manufacturing technology by introducing flexible manufacturing systems (FMS). The evidence, however, suggests that the payoffs from investing in FMS will not be adequate unless manufacturers also ensure their human resources lever the new technology. The programmable capabilities of FMS are limited to handling quickly and efficiently the more routine aspects of variable manufacturing processes. For FMS to achieve economies of scope and fulfil their promise, FMS need to be staffed by individuals who can lever FMS. These are individuals who can work with FMS, and who can go beyond the limitations of FMS by handling quickly and efficiently the less routine aspects of these manufacturing processes. To lever FMS, human resources need to be managed differently than in traditional factories. They need to be organized into self-managing teams; they need to be classified into few job categories; they need to be selected because of their FMS matching characteristics; they need to be trained; and they need to be rewarded for their varied skills and cooperation. Moreover, they need to be empowered by managers who substitute the coaching approach for the command and control approach, and who seek closer union-management relationships.

In connection with the progressive introduction of highly automated manufacturing systems and CIM systems, much attention in the last two decades has been paid to the investigation of the potential formalization of manual, routine-mental and partly also creative human activity (operator, dispatcher, designer). There has been a search for software tools that achieve individual results like the 'real' human expert mainly on the basis of symbolic considerations with the use of heuristic procedures. Decision support systems and expert systems appear to be very effective tools in the realization of the obtained algorithms and formalized decision making procedures. >

Self-Organising Electronic Institutions and Flexible Manufacturing Systems