Developing computer integrated manufacturing: Major issues and problem areas

1 - CIM — the scope

This study provides an empirical analysis of some managerial factors which are critical to the successful planning and implementation of Computer-Integrated Manufacturing (CIM) systems. CIM is viewed as an integrated computer-based information technology applications and as a strategic tool which ties together different technologies, as well as various functional areas and managerial levels. Thus, enough emphasis must be placed on communicating the company-wide goals and strategies to various functional areas and employees, particularly with regard to the CIM implementation. In this study, a number of managerial factors will be identified and factor analysis will be used to examine the technological and managerial factors.

During the last decade (from the late 1970s to the beginning of the 1990s), manufacturing systems have significantly changed. Their function and performance have altered in a period of rapid development, mainly as a result of the application of the techniques of computer science. The new systems are termed either flexible manufacturing systems (FMS) or computer- integrated manufacturing (CIM). The advance of flexible manufacturing and its related technologies has been accompanied by a number of related developments, such as flexible manufacturing of a global network type, CIM incorporating personnel functions, skill-based manufacturing, and compact flexible manufacturing cells (FMC). These all have notable influences on the system configuration and operational technologies of flexible manufacturing: perhaps as a result, there is some confusion about their terminology. A number of differing nomenclatures are used (such as FMC, FMS, flexible or factory automation (FA), CIM and enterprise automation (EA), for the same fundamental technology.

The automation of a cold-strip mill is described. The aim of the construction is discussed, and a general outline of the mill is presented. Principal technologies composing the CIM (computer integrated manufacturing) system are the following: automation, continuous process, and process-control technologies; coil tracking; and systemization of production and material-flow control. The effect of CIM is discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Strategic integrated manufacturing systems: the concept and structures

The purposes of this study are to determine (1) the frequency of use of advanced manufacturing technologies (AMTs) in south-western United States manufacturing firms, (2) which AMTs have the greatest perceived impact on value, and (3) which have been most successfully employed. The study population consisted of senior manufacturing managers of companies in SIC 34 through 39 located in six south-western states. The study determined that the most frequently used AMT was computer-aided design (CAD), used by 75% of the respondents. Manufacturing resource planning (MRP), computer numerically controlled (CNC) machining, statistical process control (SPC), and computer aided manufacturing (CAM) were used by at least one-third of the respondents. Automated process monitoring and automated material handling were the least used AMTs. Those AMTs perceived to have the greatest positive effect on producer's value are CNC machining, closed loop process control, automated process inspection, flexible manufacturing cells (FMC), robotics, computer-aided manufacturing, computer integrated manufacturing (CIM), and automated process monitoring. The AMTs could be classified into four categories based upon their effect on the two dimensions of value quality and cost. These categories were high value affecting, quality affecting, cost affecting, and low value affecting. Four of the high value affecting AMTs were among those rated as having the highest overall degree of success. However, the study found that dissonance exists between the AMTs which are most used and those which are perceived to have the greatest effect on value.

Integrating manufacturing resources planning (MRP II) with flexible manufacturing systems (FMS)

High quality and low-cost factors are among the main components of manufacturing. Nowadays, businesses need to keep up with technological innovations in order to meet these factors and survive in a competitive environment. These require the use of high-performance computer integrated manufacturing (CIM) technologies in order to manufacture products faster, inexpensively, flexibly and more efficiently. These technologies generally include computer-aided design (CAD) and computer-aided manufacturing (CAM), industrial robotics, automated material handling systems, group technology, flexible manufacturing systems (FMS), rapid prototyping (RP) operations and computer numerical controlled (CNC) machines. The main purpose of these advancements is to provide higher labour efficiency and flexibility, lower production time and a reduction of direct labour requirements. In this chapter, the effects of CIM technologies on manufacturing processes as well as product quality will be comparatively analysed. The effect of the internet of things (IoT), cyber-physical service (CPS) and cloud computing (CC) on smart manufacturing systems, which can be operated and integrated with CIM and contribute to increasing manufacturing efficiency by using information, will be revealed in detail.

Performance management of communication networks is critical for speed, reliability, and flexibility of information exchange between different components, subsystems, and sectors (e.g., factory, engineering design, and administration) of production process organizations in the environment of Computer Integrated Manufacturing (CIM). The objective is to improve the efficiency in handling various types of messages, e.g., control signals, sensor data and production orders, by on-line adjustment of the parameters of the network protocol. This paper presents conceptual design, development, and implementation of a performance management procedure for CIM applications. The performance management algorithm is formulated using the concepts of: (i) perturbation analysis of discrete event dynamic systems; (ii) stochastic approximation; and (iii) learning automata. The performance management procedure has been tested via emulation on a network testbed that is based on the Manufacturing Automation Protocol (MAP).

Some Managerial Issues Concerning Implementation and Maintenance of Flexible Manufacturing Systems- An Indian Perspective

Performance management of communication networks is critical for speed, reliability, and flexibility of information exchange between different components, subsystems, and sectors (e.g., factory, engineering design, and administration) of production process organizations in the environment of computer integrated manufacturing (CIM). Essential to this distributed total manufacturing system is the integrated communications network over which the information leading to process interactions and plant management and control is exchanged. Such a network must be capable of handling heterogeneous traffic resulting from intermachine communications at the factory floor, CAD drawings, design specifications, and administrative information. The objective is to improve the efficiency in handling various types of messages, e.g., control signals, sensor data, and production orders, by on-line adjustment of the parameters of the network protocol.

Interfacing CAD to CAPP (computer-aided process planning) is crucial to the eventual success of a fully-automated computer-integrated manufacturing (CIM) environment. Current CAD and CAPP systems are separated by a “semantic gap” that represents a fundamental difference in the ways in which they represent information. This semantic gap makes the interfacing of CAD to CAPP a non-trivial task. This paper argues that automatic feature recognition is an indispensable technique in interfacing CAD to CAPP. It then surveys the current literature on automatic feature recognition methods and systems, and analyzes their suitability as CAD/CAPP interfaces. It also describes a relatively recent automatic feature recognition method based on volumetric decomposition, using Kim’s alternating sum of volumes with partitioning (ASVP) algorithm. The paper’s main theses are: (1) that most previous automatic feature recognition approaches are ultimately based on pattern-matching; (2) that pattern-matching approaches are unlikely to scale up to the real world; and (3) that volumetric decomposition is an alternative to pattern-matching that avoids its shortcomings. The paper concludes that automatic feature recognition by volumetric decomposition is a promising approach to the interfacing of CAD to CAPP.

This paper describes the partnership SEMY Engineering, Inc. and White Oak Semiconductor formed to successfully provide automation and advanced process control (APC) solutions from a combination of proprietary and commercially available software systems. The White Oak factory objective was to implement a computer integrated manufacturing (CIM) system providing full availability of all necessary data for yield analysis and process control. Semiconductor production throughput and reliability at White Oak has significantly increased using this implementation. A large ROI (>500%) has already been realized in the lithography cell in the first year alone.

Many manufacturing companies are studying how the systematic use of computers throughout their operation can improve productivity, with the goal of achieving computer-integrated manufacturing (CIM). It is now realized that computer control should be applied to systems as a whole in addition to individual processes. A manufacturing workcell is composed of a number of stations that perform value-adding processes linked by a material-handling system and computer control. Although the cellular approach to factory automation is widely accepted, there is a shortage of commercial software for controlling cells. The cell control problem involves high level functions of production scheduling and resource management, as well as the monitoring and control of real-time processes. An intelligent control algorithm is presented that can be applied to manufacturing workcells. Since it is easier to add cell-specific knowledge to a knowledge base than to modify a conventional program, a knowledge-based implementation supports the goal of a generic controller. Results from implementing such a controller for a simulated workcell indicate that this approach merits further development.

We propose an automatic indoor furniture layout scheme based on functional area division and furniture filling. According to the function, we suppose each kind of furniture may be laid out in one or several functional areas, for example, a sofa may be located in the meeting area of a living room and a bed may be located in the sleeping area of a bedroom, etc.. Our automatic layout method divides an empty room region into several functional areas by using conditional generative adversarial networks (CGAN). We expound the learning process of the algorithm in the process of functional areas division, including the objective function construct and training process. Moreover, in order to fill furniture into a specific functional area, a learning-based furniture filling algorithm is proposed by training a fully connected network model for different kinds of functional area. Experiments show our automatic furniture layout method has its advantages in performance and effect compared with the existing methods.