DOCSLIB.ORG

Engineering Process Simulation Model Electrical Systems and Projects Engineering Process ABB Marine & Cranes

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Engineering Process Simulation Model Electrical Systems and Projects Engineering Process ABB Marine & Cranes Engineering process simulation model Electrical Systems and Projects Engineering Process ABB Marine & Cranes Bachelor’s thesis Industrial Management Autumn 2013 Adrian Badillo Sampedro ABSTRACT Unit Final Thesis Name of degree programme Industrial Management Option Author Adrian Badillo Sampedro Year 2013 Subject of Bachelor’s thesis Engineering process simulation model ABSTRACT The background for this thesis is formed by two documents: − 3AFV6036386 Engineering Process Description. − 3AFV6041649 Engineering Process Flow Chart. The purpose of the first mentioned document is to describe the project en- gineering process. The document focuses on engineering actions to meet the technical requirements of the customer and the man-hour budget of a project, on using standard products and system solutions and on support- ing commissioning. The second document is a graphical representation of the engineering pro- cess steps described in the first document. It was used as a basis for the simulation model. Both documents were needed to understand the com- plete engineering process. The aim of this thesis was to build up a simulation model of the proposed engineering process, and to define adjustable attributes for all the tasks. The process was modelled in appropriate detail to allow for the identifica- tion and calculation of the extra time invested by the resources. The engineering process was modelled using commercial discrete-event simulation software. The model was created in two phases; first the com- plete process was modelled based on existing documents, and then it was refined based on the interviews with the person of contact in the Electrical Systems and Projects Engineering Process department. Once the simula- tion model is finished, resources will be sized to reduce the extra-time in- vested in the engineering process. Therefore, the model itself is the main result of this thesis, because it al- lows for testing the complete process, and it acts as important validation for the department if any modification in the engineering process is ap- plied in the future. Keywords simulation, engineering, process, model, Simul8. Pages 117 p. + appendices 0 p. CONTENTS 1 INTRODUCTION ................................................................................................... 1 1.1 Commissioning organisation ............................................................................ 1 1.2 Aim of thesis .................................................................................................... 1 1.3 Scope of simulation model ............................................................................... 2 1.4 Research methods ............................................................................................ 2 2 QUANTITATIVE TOOL IN A DYNAMIC SYSTEM ............................................ 2 2.1 Process modelling ............................................................................................ 3 2.2 Quantitative tool .............................................................................................. 4 2.3 Stochastic model .............................................................................................. 5 2.3.1 Variability under an operational perspective ......................................... 5 2.3.2 Variability under an economical perspective ......................................... 6 2.4 Introduction to simulation ................................................................................ 7 2.4.1 Computer-based simulation models ...................................................... 8 2.4.2 Discrete event simulation ...................................................................... 9 2.5 Input data analysis .......................................................................................... 12 2.5.1 Dealing with randomness .................................................................... 13 2.5.2 Probability distribution of field data .................................................... 14 2.6 Output data analysis ....................................................................................... 15 3 SIMULATION ENGINEERING PROCESS .......................................................... 16 3.1 Simulation objectives ..................................................................................... 17 3.1.1 Given inputs ....................................................................................... 17 3.1.2 Desired outputs ................................................................................... 18 3.2 Selection of a suitable tool ............................................................................. 18 3.2.1 Arena & Simul8 comparison ............................................................... 19 3.2.2 Arena evaluation ................................................................................. 21 3.2.3 Simul8 evaluation ............................................................................... 21 3.2.4 Comparison conclusion ....................................................................... 21 3.3 Simul8 concepts ............................................................................................. 22 3.3.1 Work Item .......................................................................................... 22 3.3.2 Start Point ........................................................................................... 22 3.3.3 Queue ................................................................................................. 23 3.3.4 Activity ............................................................................................... 23 3.3.5 End Point ............................................................................................ 23 3.3.6 Routing ............................................................................................... 23 3.3.7 Resource ............................................................................................. 24 3.3.8 Group ................................................................................................. 25 3.3.9 Component ......................................................................................... 25 3.3.10 Label .................................................................................................. 25 3.3.11 Distribution ......................................................................................... 25 3.3.12 Information Store ................................................................................ 26 3.3.13 Dialog ................................................................................................. 26 3.3.14 Visual Logic ....................................................................................... 27 3.4 Data sources ................................................................................................... 27 3.4.1 Engineering Process Description ......................................................... 28 3.4.2 Engineering Process Flow Chart ......................................................... 28 3.4.3 Project Manager Course ...................................................................... 29 3.4.4 Assumptions & Estimations ................................................................ 29 4 SIMULATION MODEL MANUAL ...................................................................... 29 4.1 Nomenclature ................................................................................................. 30 4.1.1 Simulation elements ............................................................................ 31 4.1.2 Simulation objects .............................................................................. 32 4.1.3 Global Data Item ................................................................................ 35 4.2 Work flow ...................................................................................................... 37 4.2.1 Routing In ........................................................................................... 39 4.2.2 Before Selecting ................................................................................. 40 4.2.3 Routing Out ........................................................................................ 43 4.2.4 On Work Complete ............................................................................. 44 4.3 Use of Resources............................................................................................ 47 4.3.1 Responsibilities ................................................................................... 48 4.3.2 After Loading Work ............................................................................ 48 4.3.3 Travel Time ........................................................................................ 52 4.4 Use of Data .................................................................................................... 54 4.4.1 Preferences ......................................................................................... 54 4.4.2 Clock Properties ................................................................................. 55 4.4.3 Start Point Properties .......................................................................... 56 4.4.4 Links .................................................................................................. 57 4.4.5 Components ........................................................................................ 58 4.5 Custom Dialogs .............................................................................................
Load more

Recommended publications
  • Dynamic Simulation for Optimisation Solution of Manufacturing Processes
    MATEC Web of Conferences 244, 01010 (2018) https://doi.org/10.1051/matecconf/201824401010 ITEP’18 Dynamic simulation for optimisation solution of manufacturing processes Vladimíra Schindlerová1,*, Ivana Šajdlerová1, Dominika Lehocká2 1VŠB - Technical University of Ostrava, Faculty of Mechanical Engineering, 17. listopadu 2172/15, 708 33, Ostrava - Poruba, Czech Republic 2Technical University of Kosice, Faculty of Manufacturing Technologies with a seat in Presov, Bayerova 1, 080 01 Presov, Slovak Republic Abstract. One way how to study the real behaviour of industrial processes or systems in practice is to use computer simulations. We can simulate different conditions and find optimal parameters without increased risk. The right application of these parameters in practice can produce the desired results. The advantage is not only the safe verification of various variants of the simulated parameters, but also the possibility of their use in different areas of industrial practice. This article deals with an example of the use of simulation in the production of the selected automobile cooling system component. The simulation model was created to design the correct number of Kanban circuits to shorten production lead time and to reduce inter-operational supplies. The suitability of using computer simulations to optimize the production processes and systems in practice can be confirmed based on comparison of the results from the computer simulation with results achieved in practice. Keywords: Dynamic Simulation, Optimisation, Manufacturing Processes, Kanban 1 Introduction Evaluating the quality of delivered products or provided services by customers depends on the degree of fulfilment of the expected requirements whether it is the ability to deliver products or services corresponding to the customers´ ideas as for the appearance and design, correct amount, agreed delivery times or required quality at reasonable prices.
    [Show full text]
  • Discrete Event Simulation – Production Model in Simul8
    DISCRETE EVENT SIMULATION – PRODUCTION MODEL IN SIMUL8 Jakub Fousek, Martina Kuncova and Jan Fábry Department of Econometrics University of Economics in Prague W.Churchill Sq. 4, 13067 Prague 3, Czech Republic E-mail: [email protected]; [email protected]; [email protected] KEYWORDS First, a conceptual model will be created. The whole production process is divided into individual activities Discrete Event Simulation, Production Model, Radial being executed on corresponding work centers and Fans, SIMUL8. using prescribed resources. Then, a simulation model will be developed in the environment of SIMUL8. After ABSTRACT debugging the model, results obtained from the Computer simulation is a method for studying complex simulation runs should show the bottleneck parts of the systems that are not solvable with the use of standard system and possibilities of improvements. The analytical techniques. This contribution deals with the experiments will be performed with the objective to application of simulation program SIMUL8 to the suggest the management the most responsible decision. analysis of production process in company Alteko, Inc. SIMUL8 producing radial fans. The main purpose of the computer experiments is to identify the bottleneck SIMUL8 is a software package designed for Discrete processes and to suggest the management the Event Simulation or Process simulation. It has been appropriate solution. Computer experiments are aimed developed by the American firm SIMUL8 Corporation at the possibility of the parallelization of contracts in (www.simul8.com). The software has started to be used terms of the utilization of shared resources. Acceptable in 1994 and every year a new release has come into requirements for resources are recommended without being with new functions and improved functionality.
    [Show full text]
  • Sybase Powerdesigner for Information Architecture
    White Paper Sybase PowerDesigner for information architecture A White Paper by Bloor Research Authors : David Norfolk & Philip Howard Publish date : March 2012 Sybase PowerDesigner is one of the leading modelling tools in the market and the introduction of IA capabilities in version 16 makes it a strong candidate for enabling information architecture David Norfolk Sybase PowerDesigner for information architecture …bringing business and technology together Executive summary Automated business services are, ultimately, In this paper we will consider the need for, built on data; but, more than that, on data that and benefits of, implementing information we understand. That is, information is data architecture and we will discuss how Sybase that is understood in both business and techni­ PowerDesigner, Version 16, enables that pro­ cal terms. cess. Briefly, Sybase PowerDesigner has 20+ years history of providing modelling support Understanding data requires not only a know­ for database design and has more recently in­ ledge of its semantics (what the pieces of troduced support for enterprise architecture. data actually mean) and structure (entities, With version 16 the company has added a focus relationships between them and allowed on information architecture, which introduces values) but also knowledge of how it is used. a set of information architecture models for a So, information architecture (IA) provides a range of stakeholders from data analysts to documented framework that includes your business analysts around a single metadata data; the technical metadata that describes repository. Its ‘Link and Synch’ facility keeps it and is used in building databases and data all the models in synch, regardless of which access systems; and which encapsulates your one a particular stakeholder feels comfort­ knowledge of how this is (or should be) used.
    [Show full text]
  • Simulation Modeling with SIMUL8 / Kieran Concannon
    Simulation Modeling with Kieran Concannon Mark Elder Kim Hindle Jillian Tremble Stanley Tse Produced by: Simulation Solutions Copyright Visual Thinking International, 2007 Cover Design Jo-Dee Burbach Tuling This book was produced by Visual8 Corporation and printed and bound by e- impressions Inc. First published 2004 Copyright © Visual Thinking International. All rights reserved. This edition published 2007 Copyright © Visual Thinking International No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, without the prior written permission of Visual Thinking International, telephone 1-800-878-3373, email [email protected]. All trademarks are the property of their respective companies. Document Edition 4.1 Date September 2007 SIMUL8 Software Version 14.0 ISBN 0-9734285-0-3 Printed in Canada. National Library of Canada Cataloguing in Publication Simulation modeling with SIMUL8 / Kieran Concannon ... [et al.]. Includes index. ISBN 0-9734285-0-3 1. SIMUL8. 2. Computer simulation--Computer programs. I. Concannon, Kieran, 1951- QA76.9.C65S45 2003 003'.353 C2003-907459-5 About the Authors and Contributors Simulation Modeling with SIMUL8 • 1 About the Authors and Contributors Authors Kieran Concannon With a Masters in Operations Research from Birmingham University, Kieran has been developing computer simulations for over 25 years. He has played a vital role in establishing the use of simulation in production planning and execution and has been influential in the development of SIMUL8. Kieran founded and is currently the President of Visual8 Corporation, the preeminent consulting, training, and support group for SIMUL8 in North America.
    [Show full text]
  • Sybase Powerdesigner 11 Overview
    SYBASE¤ POWERDESIGNER¤ 11 OVERVIEW WHAT IS POWERDESIGNER® 11? A model driven approach to align business and IT. PowerDesigner is an enterprise modeling and design solution that empowers IT professionals to produce solutions effectively, from defining business needs to analysis and design, integrating all modern RDBMS and development for Java™, .NET, PowerBuilder® and Web Services. PowerDesigner is a unique set of modeling tools combining several standard modeling techniques: application modeling through UML, Business Process Modeling and market-leading data modeling, all supported by a powerful meta-data management solution. PRODUCT DESCRIPTION PowerDesigner is a model-driven analysis and design solution Data Modeling: PowerDesigner supports Conceptual, that aligns business and IT to enable enterprises to build Logical and Physical Data models based on Information information systems quickly and cost effectively. PowerDesigner Engineering or IDEF 1/x notation. PowerDesigner’s offers capabilities for a variety of roles and responsibility across Conceptual and Logical models provide database-independent the enterprise. PowerDesigner offers advanced teamwork and analysis level models, fully linked to multiple physical models meta-data management using a central enterprise repository for true multi-level design. and has open support for all major development platforms. PowerDesigner’s Physical models document, generate and PowerDesigner supports the following reverse engineer structures for over 45 RDBMS vendor/ modeling techniques: versions including the latest Oracle®, IBM® (including Requirements Management: PowerDesigner supports Informix® and Red Brick™ Warehouse), Microsoft (SQL requirements definitions that can be linked to any number Server and Access), Sybase (including ASE, ASA and IQ), of analysis and design models to document requirement NCR Teradata, MySQL and many more.
    [Show full text]
  • Criteria for the Evaluation of Business Process Simulation Tools
    Interdisciplinary Journal of Information, Knowledge, and Management Volume 2, 2007 Criteria for the Evaluation of Business Process Simulation Tools Vesna Bosilj-Vuksic Vlatka Hlupic and Vlatko Ceric University of Westminster University of Zagreb, Faculty of Westminster Business School, Economics and Business, London, UK Zagreb, Croatia [email protected] [email protected] [email protected] Abstract This paper focuses on a process of simulation software packages selection in the context of busi- ness process change projects. The paper presents discrete event simulation, its relation to business process modelling and examples of its practical applications in business process change projects. Features of business process simulation tools are examined, the most important simulation fea- tures are identified and the criteria for their evaluation are defined. The guidelines that could help managers in the selection of business process simulation tools are proposed. The discussion ad- dresses the limitations of the proposed guidelines. Finally, based on the conducted research and the evaluation criteria defined within the guidelines, some directions for the further improvement of business process simulation tools are given. Keywords: Business process simulation, discrete event simulation, business process change, business process modelling tools, guidelines for the evaluation of business process simulation tools Introduction In a period of continuous change in global business environments, organisations, large and small, are finding it increasingly
    [Show full text]
  • Powerdesigner 15.2
    Business Process Modeling PowerDesigner® 15.2 Windows DOCUMENT ID: DC38088-01-1520-01 LAST REVISED: February 2010 Copyright © 2010 by Sybase, Inc. All rights reserved. This publication pertains to Sybase software and to any subsequent release until otherwise indicated in new editions or technical notes. Information in this document is subject to change without notice. The software described herein is furnished under a license agreement, and it may be used or copied only in accordance with the terms of that agreement. To order additional documents, U.S. and Canadian customers should call Customer Fulfillment at (800) 685-8225, fax (617) 229-9845. Customers in other countries with a U.S. license agreement may contact Customer Fulfillment via the above fax number. All other international customers should contact their Sybase subsidiary or local distributor. Upgrades are provided only at regularly scheduled software release dates. No part of this publication may be reproduced, transmitted, or translated in any form or by any means, electronic, mechanical, manual, optical, or otherwise, without the prior written permission of Sybase, Inc. Sybase trademarks can be viewed at the Sybase trademarks page at http://www.sybase.com/detail?id=1011207. Sybase and the marks listed are trademarks of Sybase, Inc. A ® indicates registration in the United States of America. Java and all Java-based marks are trademarks or registered trademarks of Sun Microsystems, Inc. in the U.S. and other countries. Unicode and the Unicode Logo are registered trademarks of Unicode, Inc. All other company and product names used herein may be trademarks or registered trademarks of the respective companies with which they are associated.
    [Show full text]
  • Title of Paper in Brief and in Bold Capitals
    THE ROLE OF SIMULATION IN THE DEVELOPMENT OF INTELLIGENCE FOR FLEXIBLE MANUFACTURING SYSTEMS Brian Flanagan and David Walsh Engineering Technology Department, Waterford Institute of Technology. ABSTRACT Discrete event simulation has been successfully employed as an analysis tool for predicting the effect changes have on existing and hypothetical systems. This insight allows for more informed appraisals of alternatives, greatly enhancing the planning function. Simulation modelling allows microscopic analysis of complex system dynamics giving the intimate understanding required to maximise the efficiency of such systems. As well as being used to predict the future and explain the operation of complex processes, simulation models are also used in real-time control systems to provide decision support for automated (intelligent) decision makers. Current research suggests that a combination of simulation and ‘meta-heuristic’ optimisation techniques applied to analytically intractable problems can yield optimal or near optimal solutions. This paper gives a brief review of the history of discrete event simulation and discusses the role of simulation modelling in the ever-changing manufacturing environment. It pays particular attention to the importance of simulation in intelligent, highly automated, flexible manufacturing systems. It details a case study in which a simulation model and an optimisation strategy are integrated as part of an intelligent decision maker. This application implements an adaptation of the Amherst – Karlsruhe model of an automated dynamic scheduling system. KEYWORDS: (Simulation modelling, Dynamic Scheduling, FMS) 1. INTRODUCTION The idea of manufacturing industries having to re-invent themselves is by no means a new concept. As markets globalise, pressure to sustain competitiveness has become more intense.
    [Show full text]
  • Discrete Event Simulation – Model of a Call Center in Simul8 Software
    DISCRETE EVENT SIMULATION – MODEL OF A CALL CENTER IN SIMUL8 SOFTWARE Martina Kuncová, Jan Fábry and Anna Marie Klímová Department of Econometrics University of Economics in Prague W.Churchill Sq. 4, 13067 Prague 3, Czech Republic E-mail: [email protected]; [email protected]; [email protected] KEYWORDS deal with the question of trade-offs in a call center. Kuncová and Wasserbauer (2007) created a simulation Discrete event simulation, call center, SIMUL8. model for the optimization of the number of helpdesk’s operators, and for the optimization of the operator’s ABSTRACT working time. Simulation modelling is usually used when In the following text we present the simulation model of mathematical models and calculations are hard to apply a call center in the real company. As many authors show on a system with stochastic behavior. This contribution (e.g. Banks 1998; Montevecchi et al. 2007), simulation deals with the application of simulation program experiments representing different scenarios have SIMUL8 to the analysis of a call center. The main aim significant meaning for a company’s decision making. is to create a model based on the real data and afterwards to conduct two experiments to see the In the paper, we offer two experiments aimed at changes impact of changes on the functionality of the call center in the number of customers (acceding to a new and on the number of customers lost. More suitable advertisement) and in the number of operators (based on software can be used for the analysis of call centers. the closure of one call center building).
    [Show full text]
  • Lguideindex.Pdf
    Appendix H: Index A Automatic results collection. See Button, 369 Results Button click logic, 304 Abandonment, 138 Average distribution. See Access information store Distributions C distribution. See Distributions Activity based costing, 51, See B Capacity, 138 Finance Captured resource, 296 Advanced objects, 169 Batch by type, 329, 333 Cascading queues, 144 Align objects, 305 Batching, 135, 160, 534–37 Cause and effect, 82 Allowances, 155 avoid fractional values, 136 confusing, 139 Animation, 526 batch management.s8, 535 Central limit theorem, 149 resources, 262, 271 batch size, 151, 162 Changeover. See Routing-in Antithetic random numbers, 211 by label, 240 Charts. See Graphs Appointments. See Arrivals by type, 162, 241, 541 Circulate routing-out. See Routing- Arrange, 306 by type, fixed, 241 out Arrivals creating a batch, 534 Clock, 23–24, 63–80 appointment based arrivals.s8, random products with batch 24-hour clock, 68 529 size.s8, 534 choosing a time scale, 63–65 appointments, 133, 218, 529 recipe manangement.s8, 536 decimals, 66 booking appointment.s8, 530 recipes, 536 default settings, 67 flexible mechanism for, 134 results when using, 91 delay, 732 random, 132 routing-out, 250, 546 display, 67 rate, 132 transferring batches, 535 docking, 65 scheduled, 133, 218, 531 Bernoulli distribution. See format is for display only, 68 scheduled arrivals.s8, 531 Distributions go to end of warm-up period simultaneous, 135 BestFit, 203 command, 74 systems for, 528 Beta distribution. See Distributions go to simulation time time dependent rates, 217, 532 Binomial distribution. See command, 74 time of, 143 Distributions how to open, 65 Arrows. See Routing arrows Block current route, 54 items per time unit, 65 ASCII files, 506–11 Bottleneck analysis, 124 move ahead or back commands, comma-separated, 508, 510–11, Bounded distribution.
    [Show full text]
  • Discrete Event Simulation Paul Savory University of Nebraska at Lincoln, [email protected]
    University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Industrial and Management Systems Engineering Industrial and Management Systems Engineering Faculty Publications Fall 2009 Course Portfolio - Discrete Event Simulation Paul Savory University of Nebraska at Lincoln, [email protected] Follow this and additional works at: http://digitalcommons.unl.edu/imsefacpub Part of the Industrial Engineering Commons, Operational Research Commons, and the Other Operations Research, Systems Engineering and Industrial Engineering Commons Savory, Paul, "Course Portfolio - Discrete Event Simulation" (2009). Industrial and Management Systems Engineering Faculty Publications. 4. http://digitalcommons.unl.edu/imsefacpub/4 This Article is brought to you for free and open access by the Industrial and Management Systems Engineering at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Industrial and Management Systems Engineering Faculty Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Course Portfolio for IMSE 440/840 Discrete-Event Computer Simulation by Dr. Paul Savory Industrial and Management Systems Engineering University of Nebraska-Lincoln 2009 Part 1: Goal of this Portfolio Click the below video to hear Dr. Savory I have two key objectives in writing this talk about his portfolio portfolio: (1) to document my students’ learning and the effectiveness of my classroom approaches. (2) to explore approaches for how best to present documentation of my teaching and how students are meeting my expectations. Part 2: Introduction to my Course 2.1 Course Context 2.2 Course History My course, IMSE 440/840 (Discrete-Event I have taught this course 19 times in the past 15 Simulation), is our department’s only required years.
    [Show full text]
  • Supply Chain Executive Forum Examines the Growing Role of Logistics in Industry Industrial and Systems Engineering Perspectives
    Supply Chain Executive Forum Examines the Growing Role of Logistics in Industry Enterprise Systems: Industrial and Systems Engineering Perspectives Company Transformation: A Case Study of Lockheed Martin Aeronautics Company SIMULATION SOFTWARE AND SERVICES • ARENA • PROMODEL • AUTOMOD • QUEST • Enterprise Dynamics (Taylor II/ED)• SIMUL8 • KanbanSIM/PDSim • WITNESS More than 3000 Simulation projects since 1979 in Manufacturing, Logistics, and Service Industries. ADVANCED PLANNING & SCHEDULING SOFTWARE AND SERVICES • Finite Capacity Planning and Scheduling for improved customer service, reduced inventory, and better utilization of resources • High-speed creation of multi-product, multi-process production schedules • Interface to other software (SAP, Baan, etc.) and shop- floor control systems • Cost effective and web-enabled??? finite capacity scheduling solutions FULL-PAGE More than 600 installations worldwide including Automotive, Chemical, Consumer Products,ADVERTISEMENT Food Processing, Manufacturing, Electronics, and Pharmaceutical Industries. LEAN MANUFACTURING SOLUTIONS •Value Stream Mapping •Setup Time Reduction •Standardized Work •Build-in Quality •Load Leveling •Overall Equipment Effectiveness •Kaizen Events •Process Simulation •Visual Workplace •Total Production Measurements •Hands-on Shop-Floor Implementation •Lean Methods Training TECHNICAL STAFFING SERVICES Engineers on Demand! Productivity on Demand! Experience on Demand! • Industrial and Simulation Engineers (Arena, AutoMod, IGRIP, Simul8, etc.) • Mechanical and Manufacturing Engineers • Supply Chain Analysts and Software Implementers • Electrical and Computer Engineers • Designers (ALIAS, AutoCAD, CATIA, Pro-E, SDRC, UG, etc.) • IT Staffing (C/C++, Java, XML, SQL, Oracle, .NET, etc.) Production Modeling Corporation Phone: 313.441.4460 x 1131 Three Parklane Blvd, Suite 1006 West Email: [email protected] Dearborn, MI 48126 Web: www.pmcorp.com All product names mentioned in this advertisement are trademarks or registered trademarks of their respective companies.
    [Show full text]