Manufacturing vision and competitiveness

Discusses a refinement to the process by which manufacturing strategy is created. Builds on an existing strategy process (Platts, 1990) and adapts it to fit more closely within the dynamic manufacturing vision. The method for creating a manufacturing vision allows a business to do this in a two- to three-week period as part of a 10-12 week manufacturing strategy project. A conceptual model of manufacturing vision has been developed that enables practitioners to explore the factors that influenced the potential competitive contribution of manufacturing and to agree an explicit direction for change. Describes the successful application of the process in six manufacturing organizations and highlights the practical limitations of the approach.

Evaluating holonic control systems: A case study

in the last 10 years many designs and trial implementations of holonic manufacturing systems have been reported in the literature. Few of these have resulted in any industrial take up of the approach and part of this lack of adoption might be attributed to a shortage of evaluations of the resulting designs and implementations and their comparison with more conventional approaches. This paper proposes a simple approach for evaluating the effectiveness of a holonic system design, with particular focus on the ability of the system to support reconfiguration (in the face of change). A case study relating to a laboratory assembly system is provided to demonstrate the evaluation approach. Copyright © 2005 IFAC.

Enhanced integrated modelling approach to reconfiguring manufacturing enterprises

Dynamism and uncertainty are real challenges for present day manufacturing enterprises (MEs). Reasons include: an increasing demand for customisation, reduced time to market, shortened product life cycles and globalisation. MEs can reduce competitive pressure by becoming reconfigurable and change-capable. However, modern manufacturing philosophies, including agile and lean, must complement the application of reconfigurable manufacturing paradigms. Choosing and applying the best philosophies and techniques is very difficult as most MEs deploy complex and unique configurations of processes and resource systems, and seek economies of scope and scale in respect of changing and distinctive product flows. It follows that systematic methods of achieving model driven reconfiguration and interoperation of component based manufacturing systems are required to design, engineer and change future MEs. This thesis, titled Enhanced Integrated Modelling Approach to Reconfiguring Manufacturing Enterprises , introduces the development and prototyping a model-driven environment for the design, engineering, optimisation and control of the reconfiguration of MEs with an embedded capability to handle various types of change. The thesis describes a novel systematic approach, namely enhanced integrated modelling approach (EIMA), in which coherent sets of integrated models are created that facilitates the engineering of MEs especially their production planning and control (PPC) systems. The developed environment supports the engineering of common types of strategic, tactical and operational processes found in many MEs. The EIMA is centred on the ISO standardised CIMOSA process modelling approach. Early study led to the development of simulation models during which various CIMOSA shortcomings were observed, especially in its support for aspects of ME dynamism. A need was raised to structure and create semantically enriched models hence forming an enhanced integrated modelling environment. The thesis also presents three industrial case examples: (1) Ford Motor Company; (2) Bradgate Furniture Manufacturing Company; and (3) ACM Bearings Company. In order to understand the system prior to realisation of any PPC strategy, multiple process segments of any target organisation need to be modelled. Coherent multi-perspective case study models are presented that have facilitated process reengineering and associated resource system configuration. Such models have a capability to enable PPC decision making processes in support of the reconfiguration of MEs. During these case studies, capabilities of a number of software tools were exploited such as Arena®, Simul8®, Plant Simulation®, MS Visio®, and MS Excel®. Case study results demonstrated effectiveness of the concepts related to the EIMA. The research has resulted in new contributions to knowledge in terms of new understandings, concepts and methods in following ways: (1) a structured model driven integrated approach to the design, optimisation and control of future reconfiguration of MEs. The EIMA is an enriched and generic process modelling approach with capability to represent both static and dynamic aspects of an ME; and (2) example application cases showing benefits in terms of reduction in lead time, cost and resource load and in terms of improved responsiveness of processes and resource systems with a special focus on PPC; (3) identification and industrial application of a new key performance indicator (KPI) known as P3C the measuring and monitoring of which can aid in enhancing reconfigurability and responsiveness of MEs; and (4) an enriched modelling concept framework (E-MUNE) to capture requirements of static and dynamic aspects of MEs where the conceptual framework has the capability to be extended and modified according to the requirements. The thesis outlines key areas outlining a need for future research into integrated modelling approaches, interoperation and updating mechanisms of partial models in support of the reconfiguration of MEs.

Production planning of multi-stage multi-option seru production systems with sustainable measures

With the concerns over climate change and the escalation in worldwide population, sustainable development attracts more and more attention of academia, policy makers, and businesses in countries. Sustainable manufacturing is an inextricable measure to achieve sustainable development since manufacturing is one of the main energy consumers and greenhouse gas contributors. In the previous researches on production planning of manufacturing systems, environmental factor was rarely considered. This paper investigates the production planning problem under the performance measures of economy and environment with respect to seru production systems, a new manufacturing system praised as Double E (ecology and economy) in Japanese manufacturing industries. We propose a mathematical model with two objectives minimizing carbon dioxide emission and makespan for processing all product types by a seru production system. To solve this mathematical model, we develop an algorithm based on the non-dominated sorting genetic algorithm II. The computation results and analysis of three numeral examples confirm the effectiveness of our proposed algorithm. © 2014 Elsevier Ltd. All rights reserved.

Re-engineering Manufacturing for Sustainability

This edited volume presents the proceedings of the 20th CIRP LCE Conference, which cover various areas in life cycle engineering such as life cycle design, end-of-life management, manufacturing processes, manufacturing systems, methods and ...

Networks in small manufacturing firms

Fuller-Love, Nerys, and Thomas, Esyllt, 'Networks in small manufacturing firms', Journal of Small Business and Enterprise Development (2005) 11(2) pp.244-253 RAE2008

A Structured Approach to Simulate Manufacturing System In Virtual Environment

Nowadays, the realization of the Virtual Factory (VF) is the strategic goal of many manufacturing enterprises for the coming years. The industrial scenario is characterized by the dynamics of innovations increment and the product life cycle became shorter. Furthermore products and the corresponding manufacturing processes get more and more complex. Therefore, companies need new methods for the planning of manufacturing systems.
To date, the efforts have focused on the creation of an integrated environment to design and manage the manufacturing process of a new product. The future goal is to integrate Virtual Reality (VR) tools into the Product Lifecycle Management of the manufacturing industries.
In order to realize this goal the authors have conducted a study to perform VF simulation steps for a supplier of Industrial Automation Systems and have provided a structured approach focusing on interaction between simulation software and VR hardware tools in order to simulate both robotic and
manual work cells.
The first results of the study in progress have been carried out in the VR Laboratory of the Competence Regional Centre for the qualification of the Transportation Systems that has been founded by Campania Region.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.