Enhancing Facility Layout via Ant Colony Technique (Act)

Cellular manufacturing systems optimization is investigated and manipulated using artificial intelligent (AI) approach combining facility layout and group technology scope. This research applied the ANT COLONY technique  (ACT) optimization where this process was inspired by the real ants and how they move and build colonies by avoiding obstacle and simulate the process to get a procedure that can be adopted on this optimization process. In this research the problem goes in two way first the theory that take account the positions of machines inside the plant and its equations of controlling and second is the routing of part during product life cycle then execute results and applying it on factory configuration. The application of Ants system was carried out on industrial factory of electrical motor where all data was taken from the factory depending on the position and sequence of operations took place. Results were carried out in a way that depending on the showing site plan configurations for each stage and studying the iteration curve response to the parameters changes while testing the system during different environments. The results show high flexibility in ACS (Ant colony system) with fast response and high reduction in the distance crossed by the product part that reached 500m. The ratio of the reduction is 0.625. Keyword: Artificial intelligent (AI), Ant colony (AC), pheromone, genetic algorithm, facility layout, cell manufacturing (CM)

Recent developments and future trends of industrial agents

The agent technology provides a new way to design and engineer control solutions based on the decentralization of control over distributed structures, addressing the current requirements for modern control systems in industrial domains. This paper presents the current situation of the development and deployment of agent technology, discussing the initiatives and the current trends faced for a wider dissemination and industrial adoption, based on the work that is being carried out by the IEEE IES Technical Committee on Industrial Agents

Optimization of material transportation system for factory logistic

Material transportation system (MTS) often being used to move materials inside a factory, warehouse, or other facility. The five main types of equipment are industrial trucks, automated guided (AGV) vehicles, rail-guided vehicles, conveyors, and hoist and cranes. This report focused on AGV where the optimization of MTS is further studied. Applying an AGVs in logistic factory may help in improving the efficiency in material flow and distribution among workstation at right time and right place. The main objective of this project is to study transportation requirement in a factory which consist of dynamic factors. The used of dynamic system in modelling gives an advantages in term of flexibility for changes of orders, unexpected machine or equipment failure, production delays, and other decisions then feedback to alter inventories and backlogs. This report present the method to organize and analyze the movement of AGV in warehouse area to obtain the optimum number of AGVs required in the warehouse to fulfill all the task given by simulation software. Anylogic software is being used to build a simulation model and analyzed the system performance. The obtained results was the optimization of MTS for factory logistic which produce effective material handling system and creates the systematic handling system in warehouse. By manipulating number of AGV, system throughput and cycle time being observed. Data obtained from simulation being compared as number of AGV had change. Minitab 17 software are used to create statistical graph in 2D and 3D surface in order to analyze and evaluate the results

Manufacturing Lead Time Estimation with the Combination of Simulation and Statistical Learning Methods

In the paper, a novel method is introduced for selecting tuning parameters improving accuracy and robustness for multi-model based prediction of manufacturing lead times. Prediction is made by setting up models using statistical learning methods (multivariate regression); trained, validated and tested on log data gathered by manufacturing execution systems (MES). Relevant features, i.e., the predictors most contributing to the response, are selected from a wider range of system parameters. The proposed method is tested on data provided by a discrete event simulation model (as a part of a simulation-based prediction framework) of a small-sized flow-shop system. Accordingly, log data are generated by simulation experiments, substituting the function of a MES system, while considering several different system settings (e.g., job arrival rate, test rejection rate). By inserting the prediction models into a simulation-based decision support system, prospective simulations anticipating near-future deviations and/or disturbances, could be supported. Consequently, simulation could be applied for reactive, disturbance-handling purposes, and, moreover, for training the prediction models. (C) 2015 The Authors. Published by Elsevier B.V

Progress in Material Handling Research: 2012

Table of Content

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

A distribution network design for fast-moving consumer goods

A distribution network design of fast-moving consumer goods ensures distribution of products in an effective manner by giving  maximum customers’ satisfaction and minimum distribution cost. The study evaluates the distribution through direct shipment and the use of intermediate shipment for distribution of products from plant to depots. A real-life case study in Southwestern Nigeria was defined and solved as a linear programming model to minimise total cost of distribution from plant to the depots with consideration of four routing options. The results show that distribution through intermediaries gives a better solution than routing option with  direct shipment. The best routing option with intermediate points when compared with the routing option with direct shipment gives a savings of 1,819,490.00 Naira which translates to 13.46% cost savings. The study shows that the location of intermediaries is a key decision in distribution network design and that the intermediaries add value to the distribution networks in supply chain. Keywords: Distribution network; Supply chain design; Fast-moving consumer goods; Linear programmin