A genetic algorithm approach to designing and modelling of a multi-functional fractal manufacturing layout

A dynamic and optimal shop floor design, modelling and implementation is key to achieving successful Fractal Manufacturing System (FrMS). To build adaptive and fault-tolerant fractal layout, attention is paid to issues of shop floor planning, function layout, determination of capacity level, cell composition planning and flow distances of products. A full fledged FrMS. layout is multi-functional and is capable of producing a variety of products with minimal reconfiguration. This paper is part and a progression of an on-going project whereby Genetic Algorithm (GA) is adopted to design and model a flexible and multi-functional FrMS floor layout. GA is used in the project for modeling and simulation. The design implementation is done using MATLAB. The result is a fault tolerant configuration that self-regulates and adapts to unpredictable changes in the manufacturing environment arising from lead time reduction pressure, inventories, product customization and other challenges of a dynamic and volatile operational environment

Fractal architecture for 'leagile' networked enterprises.

The manufacturing environment and markets in recent times are becoming increasingly dynamic, diverse and unpredictable, due mainly to fast evolution of products and technology, erratic customer behaviour and high consumerism and an increasingly shorter lead-time. The burden of the impact falls on organisational structures built on centralized, rigid manufacturing architecture, because they cannot cope or adapt to the highly uncertain or unpredictable nature of the market. Enterprises who wish to survive these challenges need to rethink their business and manufacturing models, and most importantly reinvent their tactical, operational and organizational formulas to leverage their strategic long term visions.Newer manufacturing systems to curb the effects of this upheaval have to promote an entirely decentralised, flexible, distributed, configurable and adaptable architecture to ameliorate this condition. Many philosophies are proposed and studied towards planning, monitoring, and controlling the 21st century manufacturing system. These include - Bionic manufacturing system (BMS), Holonic manufacturing system (HMS), Fractal manufacturing system (FrMS), Responsive manufacturing etc.This research program focuses on the FrMS, which has vast conceptual advantageous features among these new philosophies, but its implementation has proved very difficult. FrMS is based on autonomous, cooperating, self-similar agent called fractal that has the capability of perceiving, adapting and evolving with respect to its partners and environment. The fractal manufacturing configuration uses self regulating, organisational work groups, each with identical goals and within its own area of competence to build up an integrated, holistic network system of companies. This network yields constant improvement as well as continuous checks and balances through self-organising control loops. The study investigates and identifies the nature, characteristic features and feasibility of this system in comparison to traditional approaches with a detailed view to maximising the logistical attribute of lean manufacturing system and building a framework for 'leagile' (an integration of lean and agile solutions) networked capabilities. It explores and establishes the structural characteristic potentials of Fractal Manufacturing Partnership (FMP), a hands-on collaboration between enterprises and their key suppliers, where the latter become assemblers of their components while co-owning the enterprise's facility, to create and achieve high level of responsiveness. It is hoped that this architecture will drive and harness the evolution from a vertically integrated company, to a network of integrated, leaner core competencies needed to tackle and weather the storm of the 21st century manufacturing system

Fractal architecture for leagile networked enterprises

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Genetic algorithm approach to modelling fractal manufacturing layout

Fractal Manufacturing System (FrMS) basically structurally builds up from units called 'fractals' or fractal objects which are independent entities and contain essential features and congenital attributes of the entire manufacturing configuration. They can selfadapt quickly to dynamic changes in an unpredictable manufacturing environment. They are also self regulating and fall under organizational work groups, each within its own area of competence. An optimal shop floor design and implementation is key and an integral part of achieving a successful FrMS. and is concerned with issues of shop floor planning, arrangement and function layout. The fractal shop floor layout develops from individual cells and is conceptually capable of producing a variety of products with minimal reconfiguration. Keen attention is paid to determination of capacity level, cell composition and flow distances of products. In this paper, Genetic Algorithm (GA) is adopted to efficiently and effectively design flexible FrMS shop floor layout, needed in agile manufacturing system to cope with new and dynamic manufacturing environments that need to adapt to changing products and technologies. Its stochastic search algorithm is used in simulating natural evolutionary process techniques, which in turn solves the many FrMS combinatorial optimization problems. The design implementation is done using MATLAB. The end result interestingly is a fault tolerant structure that is better suited to survive and stand the pressure for lead time reduction and inventories, product customization and challenges of a dynamic and unpredictable operational environment

Supplier selection criteria in fractal supply network

Original Equipment Manufacturers (OEMs) collaborate with their key suppliers in a new form of hands-on partnership. The Fractal supply network is distinct from the traditional supply chain because of the inherent congenital fractal characteristics. This paper uses the Analytic Hierarchy/Network Process (AH/NP) approach to provide a strict methodology and criteria ranking in the complicated decision-making process of exploring the suitability, selection and maintenance of few, albeit reliable and high quality suppliers prior to going into the Fractal Manufacturing Partnership (FMP). Selecting the right set of suppliers without undermining essential competitive factors and material costs is of strategic importance in forming this alliance and could help or hinder the inherent strength in the collaboration. The outcome from this research project is a simple, systematic, logical and mathematical guide to user of OEMs in making robust and informed supplier selection decision prior to going into FMP from a fractal supply network perspective