Distribution of machine information using Blackboard designed component for remote monitoring of reconfigurable manufacturing systems

A blackboard-based design for a system component called the "Broadcaster" is described in this paper. It supports remote monitoring of reconfigurable manufacturing systems using a novel system architecture coupled with the Component-Based system paradigm. The design of this component has been evaluated using a case study on a web services-enabled test rig funded by the Ford Motor Company, U. K. The test rig has been implemented using a fully distributed control device called FTB, designed by the Schneider Electric Company. Evaluation of this component has been carried out using three scenario test cases which demonstrate the potentials offered when deploying this solution to a real production environment. The system component not only operates in a heterogeneous reconfigurable manufacturing environment, offering a vendor-independent solution to monitoring machines, but it also supports remote monitoring of the machines throughout their development and management lifecycles

Space benefits: The secondary application of aerospace technology in other sectors of the economy

Benefit cases of aerospace technology utilization are presented for manufacturing, transportation, utilities, and health. General, organization, geographic, and field center indexes are included

The re-innovation of Ford Motor Company to a sustainable lean enterprise.

For many years the concept of Lean Manufacturing has been applied in automotive development as a tool to refine the manufacturing practices to the greatest efficiency possible through waste reduction. Continuous Improvement is a quality innovation process that supports this objective, based on the manufacturing pillar – work processes and scientific experiments must be controlled and constantly modified and improved by the people who do, and are accountable for the work. Continuous Improvement implicitly implies the understanding and recognition of what is a problem and problem solving techniques used to formulate the best countermeasures to those problems. The process of Lean Manufacturing embraces a philosophy of excellence, elimination of waste on value-added operations, employee involvement, and continuous improvement. It is a journey, an on-going process that results in improved customer satisfaction and hence corporate profits. Profit is the reward for customer satisfaction. Increase customer satisfaction and your rewards are higher profits. This is the best method to maintain or increase market share. Understanding the basic hierarchy and philosophy of how to increase profits is essential to creating a sustainable lean enterprise. The following structures process outlines the basic questions and answers for any company to ask itself: Process to Sustained Success (chart). This thesis is about Ford Motor Company getting back to its roots, the heritage it started with the development of the moving assembly line and the original concept of Lean Manufacturing. This paper will focus on the creative steps outlined in the Process to Sustained Success procedure toward the journey of Lean Manufacturing. In addition, the current state of production processes, and recommended specific corrective actions for the re-innovation of Ford Motor Company to a sustained lean enterprise in a modern era will be discussed. Questions will be asked and answered such as: Can Ford achieve sustained success implementing The Way Forward plan, or does The Way Forward [16] plan need to incorporate the Process to Sustained Success to meet Ford\u27s long-term goals? The benchmark company for comparison is Toyota Motor Manufacturing Corporation

Transitioning to a Lean Enterprise: A Guide for Leaders, Volume I, Executive Overview

This Transition-To-Lean Guide is intended to help your enterprise leadership navigate your enterprise’s challenging journey into the promising world of “lean.” You have opened this guide because, in some fashion, you have come to realize that your enterprise must undertake a fundamental transformation in how it sees the world, what it values, and the principles that will become its guiding lights if it is to prosper — or even survive — in this new era of “clock-speed” competition. However you may have been introduced to “lean,” you have undertaken to benefit from its implementation

Adapter module for self-learning production systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e ComputadoresThe dissertation presents the work done under the scope of the NP7 Self-Learning project regarding the design and development of the Adapter component as a foundation for the Self-Learning Production Systems (SLPS). This component is responsible to confer additional proprieties to production systems such as lifecycle learning, optimization of process parameters and, above all, adaptation to different production contexts. Therefore, the SLPS will be an evolvable system capable to self-adapt and learn in response to dynamic contextual changes in manufacturing production process in which it operates. The key assumption is that a deeper use of data mining and machine learning techniques to process the huge amount of data generated during the production activities will allow adaptation and enhancement of control and other manufacturing production activities such as energy use optimization and maintenance. In this scenario, the SLPS Adapter acts as a doer and is responsible for dynamically adapting the manufacturing production system parameters according to changing manufacturing production contexts and, most important, according to the history of the manufacturing production process acquired during SLPS run time.To do this, a Learning Module has been also developed and embedded into the SLPS Adapter. The SLPS Learning Module represents the processing unit of the SLPS Adapter and is responsible to deliver Self-learning capabilities relying on data mining and operator’s feedback to up-date the execution of adaptation and context extraction at run time. The designed and implemented SLPS Adapter architecture is assessed and validated into several application scenario provided by three industrial partners to assure industrial relevant self-learning production systems. Experimental results derived by the application of the SLPS prototype into real industrial environment are also presented

A component-based virtual engineering approach to PLC code generation for automation systems

In recent years, the automotive industry has been significantly affected by a number of challenges driven by globalisation, economic fluctuations, environmental awareness and rapid technological developments. As a consequence, product lifecycles are shortening and customer demands are becoming more diverse. To survive in such a business environment, manufacturers are striving to find a costeffective solution for fast and efficient development and reconfiguration of manufacturing systems to satisfy the needs of changing markets without losses in production. Production systems within automotive industry are vastly automated and heavily rely on PLC-based control systems. It has been established that one of the major obstacles in realising reconfigurable manufacturing systems is the fragmented engineering approach to implement control systems. Control engineering starts at a very late stage in the overall system engineering process and remains highly isolated from the mechanical design and build of the system. During this stage, control code is typically written manually in vendor-specific tools in a combination of IEC 61131-3 languages. Writing control code is a complex, time consuming and error-prone process. [Continues.

Operator interfaces for the lifecycle support of component based automation systems

Current manufacturing automation systems (specifically the powertrain sector) have been facing challenges with constant pressures of globalisation, environmental concerns and ICT (Information and Communication Technology) innovations. These challenges instigate new demands for shorter product lifecycles and require customised products to be manufactured as efficiently as possible. Manufacturing systems must therefore be agile to remain competitive by supporting frequent reconfigurations involving distributed engineering activities. [Continues.

An analysis of South African automotive supplier parks from a supply chain perspective with specific reference to the Rosslyn Automotive Supplier Park

M. Com. (Logistics Management)The opening of the first dedicated Supplier Park by Seat adjacent to its Abrera assembly facility in 1992, in many ways, marked the beginning of a global trend. Since then, more than forty parks in various configurations have been established around the world. Initially, this trend was mostly confined to Europe but the Supplier Park concept quickly gained momentum in newly industrialised countries like Brazil and, more recently, the USA and South Africa (Reichhart & Holweg, 2007: 52). The world’s automotive industry is a vital part of the workings of the global economy and the wellbeing of the world’s citizens (OICA, n.d.). According to the International Organisation of Motor Vehicle Manufacturers (OICA, n.d.), the world’s automotive industry manufactured over 66 million cars, vans, trucks and buses in 2005 which is equivalent to a global turnover of close to € 2 trillion. If vehicle manufacturing were a country, it would be the sixth largest economy in the world requiring the direct employment of nearly eight million people in manufacturing the vehicles and the parts that go into them. This is more than 5% of the world’s total manufacturing employment. In addition to these direct employees, many more people are employed indirectly in related manufacturing and service provision industries (OICA, n.d.)

A design methodology for automotive component manufacturing systems

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management, 1998.Includes bibliographical references (p. 93-94).by Brian Klippel.M.B.A.S.M