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Logistics Systems Engineer – Interdisciplinary Competence
PAPER LOGISTICS SYSTEMS ENGINEER – INTERDISCIPLINARY COMPETENCE MODEL FOR MODERN EDUCATION Logistics Systems Engineer – Interdisciplinary Competence Model for Modern Education http://dx.doi.org/10.3991/ijep.v5i2.4578 Tarvo Niine and Ott Koppel Tallinn University of Technology, Tallinn, Estonia Abstract—Logistics is an interdisciplinary field of study. However, based on research of university curricula, it is Modern logisticians need to integrate business management observed that the field of logistics education does not and administration skills with technology design, IT systems include engineering aspects to enough extent. This is both and other engineering fields. However, based on research of in terms of technologies as well as the systematic nature of university curricula and competence standards in logistics, engineering thinking. Large proportion of logistics the engineering aspect is not represented to full potential. curricula are focused on business administration with only There are some treatments of logistician competences which selected engineering topics touched, usually focusing on relate to engineering, but not a modernized one with wide- case studies of implementation benefits rather than how to spread recognition. This paper aims to explain the situation specifically design, develop such technologies and to re- from the conceptual development point of view and suggests engineer processes to accommodate with the changes. In a competence profile for “logistics system engineer”, which terms of logistics system design and underlying thought introduces the viewpoint of systems engineering into processes, the approach could often benefit from being logistics. For that purpose, the paper analyses requirements more systematic. of various topical competence models and merges the introductory competences of systems engineering into Similar gap can be observed on the level of competence logistics. -
Industrial and Systems Engineering (ISE)
Lehigh University 2021-22 1 Industrial and Systems Engineering (ISE) Courses ISE 224 Information Systems Analysis and Design 3 Credits ISE 100 Industrial Employment 0 Credits An introduction to the technological as well as methodological Usually following the junior year, students in the industrial engineering aspects of computer information systems. Content of the course curriculum are required to do a minimum of eight weeks of practical stresses basic knowledge in database systems. Database design and work, preferably in the field they plan to follow after graduation. A evaluation, query languages and software implementation. Students report is required. Must have sophomore standing. that take CSE 241 cannot receive credit for this course. ISE 111 Engineering Probability 3 Credits ISE 226 Engineering Economy and Decision Analysis 3 Credits Random variables, probability models and distributions. Poisson Economic analysis of engineering projects; interest rate factors, processes. Expected values and variance. Joint distributions, methods of evaluation, depreciation, replacement, breakeven covariance and correlation. analysis, aftertax analysis. decision-making under certainty and risk. Prerequisites: MATH 022 or MATH 096 or MATH 032 or MATH 052 Prerequisites: ISE 111 or MATH 231 or IE 111 Can be taken Concurrently: ISE 111, MATH 231, IE 111 ISE 112 Computer Graphics 1 Credit Introduction to interactive graphics and construction of multiview ISE 230 Introduction to Stochastic Models in Operations representations in two and three dimensional space. Applications in Research 3 Credits industrial engineering. Must have sophomore standing in industrial Formulating, analyzing, and solving mathematical models of real- engineering. world problems in systems exhibiting stochastic (random) behavior. Discrete and continuous Markov chains, queueing theory, inventory ISE 121 Applied Engineering Statistics 3 Credits control, Markov decision process. -
Industrial Engineering and Management M.Sc. ()
Module Handbook Industrial Engineering and Management M.Sc. SPO 2015 Winter term 2021/22 Date: 30/09/2021 KIT DEPARTMENT OF ECONOMICS AND MANAGEMENT KIT – The Research University in the Helmholtz Association www.kit.edu Table Of Contents Table Of Contents 1. General information ....................................................................................................................................................................................................... 13 1.1. Structural elements .......................................................................................................................................................................................................13 1.2. Begin and completion of a module .......................................................................................................................................................................... 13 1.3. Module versions ..............................................................................................................................................................................................................13 1.4. General and partial examinations ............................................................................................................................................................................13 1.5. Types of exams ............................................................................................................................................................................................................... -
Major Factors That Influence the Employment Decisions of Generation X Consulting Engineers
Old Dominion University ODU Digital Commons Engineering Management & Systems Engineering Management & Systems Engineering Theses & Dissertations Engineering Spring 2002 Major Factors That Influence the Employment Decisions of Generation X Consulting Engineers Robert William Mayfield Old Dominion University Follow this and additional works at: https://digitalcommons.odu.edu/emse_etds Part of the Engineering Commons, Organizational Behavior and Theory Commons, and the Work, Economy and Organizations Commons Recommended Citation Mayfield, Robert W.. "Major Factors That Influence the Employment Decisions of Generation X Consulting Engineers" (2002). Master of Science (MS), Thesis, Engineering Management & Systems Engineering, Old Dominion University, DOI: 10.25777/t41p-rd52 https://digitalcommons.odu.edu/emse_etds/102 This Thesis is brought to you for free and open access by the Engineering Management & Systems Engineering at ODU Digital Commons. It has been accepted for inclusion in Engineering Management & Systems Engineering Theses & Dissertations by an authorized administrator of ODU Digital Commons. For more information, please contact [email protected]. MAJOR FACTORS THAT INFLUENCE THE EMPLOYMENT DECISIONS OF GENERATION X CONSULTING ENGINEERS bv Robert William Mayfield B.S. March 1994, The Ohio State University A Thesis Submitted to the Faculty o f Old Dominion University in Partial Fulfillment o f the Requirement for the Degree of MASTER OF SCIENCE ENGINEERING MANAGEMENT OLD DOMINION UNIVERSITY May 2002 Approved by: Charles Keating (Direct Paul Kauffmai ember) Andres Sousa-Poza (Member) Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT MAJOR FACTORS THAT INFLUENCE THE EMPLOYMENT DECISIONS OF GENERATION X CONSULTING ENGINEERS Robert William Mayfield Old Dominion University. 2002 Director: Dr. Charles Keating The purpose of this research was to study Generation X consulting engineers (those bom between the years 1964 and 1980) in Lynchburg. -
Novel Substructural Health Monitoring Method Without Interface Measurements Using State Space Analysis and Extended Kalman Filtering
Novel Substructural Health Monitoring Method without Interface Measurements using State Space Analysis and Extended Kalman Filtering by Arianne Layard Muelhausen Under the Supervision of Prof. Brock Hedegaard A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE (Civil and Environmental Engineering) at the University of Wisconsin-Madison 2018 Contents 1 Introduction 2 2 Literature Review 4 3 Methodology 8 3.1 State Space Analysis . .8 3.2 Kalman Filter . .9 3.3 Extended Kalman Filter . 11 3.4 Substructural Identification using Extended Kalman Filtering . 12 3.4.1 Global Equation of Motion . 13 3.4.2 Substructural Equation of Motion . 14 3.4.3 State Space Formulation: State Transition Equation . 17 3.4.4 State Space Formulation: Measurement Equation . 18 3.4.5 Implementation of Extended Kalman Filter . 19 3.5 Methodology Step-by-Step Summary . 24 4 Results 25 4.1 Model Description . 25 4.2 Case One: All DOFs Measured . 26 4.3 Case Two: All Interface and Some Interior DOFs Measured . 29 4.4 Case Three: Some Interface and Some Interior DOFs Measured . 31 4.5 Case Four: No Interface and Some Interior DOFs Measured . 38 4.6 Discussion on Limitations of Method . 40 5 Conclusion 41 6 Work Cited 42 1 1 Introduction Structural Health Monitoring (SHM) at its core is a process to identify damage, defined as either material or geometric change, of a system that negatively affects the systems performance[7]. SHM seeks to address four questions: (Level 1) Detection: Is damage present? (Level 2) Localization: What is the probable location of damage? (Level 3) Assessment: What is the severity of the damage? (Level 4) Prognosis: What is the remaining service life of the damaged system? SHM can be used to monitor structures affected by external stimuli, long-term movement, ma- terial degradation, or demolition. -
Springer.Comspringer.Com.Cn
ABCD springer.comspringer.com.cn Springer 工程學 2010年 上半年度 ABCD springer.com Don’t wait! Sign up today! Accelerate your business and join us, using all of the tools Springer has created to keep you informed tailored to your specific needs 7 Sign up today for the Springer NEWS online at springer.com/springeralerts/booksellers 7 Create your own catalogs quickly and easily using the SIGN UP ! Springer Customized Catalog at springer.com/customizedbooklist 7 Keep track of journals that have transferred to us at springer.com/forgetmenot 7 Learn more about the full range of our new, forthcoming and just released titles 7 Get notice about Price Changes and Special Offers and last but not least… 7 Make use of the electronic Book Order Form and email your order directly to Springer Customer Service Center Sign up at springer.com/bookseller springer.com 014262x springer.com Table of Contents 1 Engineering Aerospace Technology and Astronautics ................................................................................................. 2 Appl. Mathematics / Computational Methods of Engineering .......................................................... 3 Automotive Engineering ......................................................................................................................... 5 Biomedical Engineering ............................................................................................................................ 6 Building Construction, HVAC, Refrigeration ..................................................................................... -
Multivariate Statistical Process Monitoring Using Classical
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Newcastle University eTheses Multivariate Statistical Process Monitoring Using Classical Multidimensional Scaling Prepared by: Mohd Yusri Mohd Yunus A Thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy School of Chemical Engineering and Advanced Materials Newcastle University UK May 2012 ABSTRACT A new Multivariate Statistical Process Monitoring (MSPM) system, which comprises of three main frameworks, is proposed where the system utilizes Classical Multidimensional Scaling (CMDS) as the main multivariate data compression technique instead of using the linear- based Principal Component Analysis (PCA). The conventional method which usually applies variance-covariance or correlation measure in developing the multivariate scores is found to be inappropriately used especially in modelling nonlinear processes, where a high number of principal components will be typically required. Alternatively, the proposed method utilizes the inter-dissimilarity scales in describing the relationships among the monitored variables instead of variance-covariance measure for the multivariate scores development. However, the scores are plotted in terms of variable structure, thus providing different formulation of statistics for monitoring. Nonetheless, the proposed statistics still correspond to the conceptual objective of Hotelling’s T2 and Squared Prediction Errors (SPE). The first framework corresponds to the original -
Towards a Strategic Management Framework for Engineering of Organizational Robustness and Resilience
Towards a Strategic Management Framework for Engineering of Organizational Robustness and Resilience Der Rechts- und Wirtschaftswissenschaftlichen Fakultät / dem Fachbereich Wirtschafts- und Sozialwissenschaften der Friedrich-Alexander-Universität Erlangen-Nürnberg zur Erlangung des Doktorgrades Dr. rer. pol. vorgelegt von Florian Maurer, MA aus Bregenz, Österreich Als Dissertation genehmigt von der Rechts- und Wirtschaftswissenschaftlichen Fakultät / vom Fachbereich Wirtschafts- und Sozialwissenschaften der Friedrich-Alexander-Universität Erlangen-Nürnberg Promotionstermin: .. Tag der mündlichen Prüfung: .. Vorsitzende/r des Promotionsorgans: Prof. Dr. Markus Beckmann Gutachter/in: Prof. Dr. Kathrin M. Möslein Prof. Dr. Ulrike Lechner Abstract I Abstract The concepts of organizational robustness and resilience are essential to organizations to withstand internal and external dynamics, risks, uncertainties and crisis. These concepts enable organizations to innovate within these adverse situation and to find a better position before the occurrence of events. Nevertheless, these concepts are less understood in Service Science research. Main focus within this theory is still on joint co-creation of value in service networks and less on innovation from organizational crisis situation. This dissertation at hand investigates into the concepts of organizational robustness and resilience from a theoretical and empirical perspective. Both perspectives are antecedent to design, develop and engineer the Strategic Management Framework for Engineering -
Supply Chain Engineering
Supply Chain Engineering Marc Goetschalckx Errata First Edition, Springer, 2011. Last updated 19-May-14 5:45:00 PM Foreword 05-Sep-2011 Replace “missing” by “mission’ in line 4. 27-Aug-2011 Replace “breath-first” by “breadth-first”. Note that this error also appears in the introductory description on Internet sites such as Amazon, but has already been corrected in the printed version. Introduction 18-May-2014 On page 18, replace “disposal time is the required” with “disposal time is the time required”. 09-Dec-2011 In the References on page 14, reference 2, replace “upply chain” with “supply chain”. Update publisher information to “Pitman Publishing, London.” Page 4, replace first sentence with “For an organization to become a long term component of a supply chain requires that the relationship between them is beneficial in the long run for the organization and for the rest of the supply chain, i.e. it is a win-win relationship.” Page 4, first paragraph, change “In the manufacturing industries, examples are” to “In the manufacturing industries, examples of supply chains are”. 31-Aug-2011 In Figure 1.5, change “Stratetic” to “Strategic” in the top left cell of the matrix. Engineering Planning and Design 18-May-2014 On page 30, replace “recyclable materials collected for” with “recyclable materials collected from”. On page 55, replace “higher- level” with “higher-level” without the extra space. 24-Oct-2012 On page 34, second paragraph, replace “articles and book has been published” with “articles and books have been published”. On page 38, last paragraph, replace “There exist a separation” with “There exists a separation”. -
MS in Advanced and Intelligent Manufacturing (AIM)
Proposal for New Program MS in Advanced and Intelligent Manufacturing (AIM) Graduate School of Engineering AIM MS Proposal Led & Prepared by Sagar Kamarthi Intended AIM MS Co-directors to be Hongli ‘Julie’ Zhu and Xiaoning ‘Sarah’ Jin Nov 20, 2020 1 EXECUTIVE SUMMARY In the last five years, the United States has seen a resurgence in advanced manufacturing fueled in part by the creation of 14 National Network of Manufacturing Innovation Institutes. The US government and industry have invested several billion dollars to revitalize advanced manufacturing in the US. As a result, all stakeholders including industry, academia, research labs, and government agencies have been forming strong partnerships to rapidly transfer science and technology into manufacturing high-tech products and processes. To meet the current and projected demand for engineers, researchers, and scientists trained in advanced and smart manufacturing and leverage Northeastern’s recognized research and development in nano and microscale manufacturing, smart manufacturing, and data analytics, the College of Engineering (COE) proposes to start a new graduate program, MS in Advanced and Intelligent Manufacturing (AIM). This program will enable students to acquire the necessary engineering, analytical and research skills to design, supervise, and manage advanced and manufacturing facilities and projects in industry, government or academia. Figure 1 depicts an infographic of advanced and smart manufacturing1. The program will address conventional manufacturing as well as advanced manufacturing. Conventional manufacturing covers topics such metal removal, forming, casting, and particulate processes. In contrast advanced manufacturing covers topics such as nanomanufacturing, fabrication and printing of micro and nano devices, additive 3D printing of parts, electronics, sensors, medical, materials and energy applications. -
On Simulation of Cross Correlated Random Fields Using Series Expansion Methods
ENGINEERING MECHANICS 2009 National Conference with International Participation pp. 1431–1443 Svratka, Czech Republic, May 11 – 14, 2009 Paper #139 ON SIMULATION OF CROSS CORRELATED RANDOM FIELDS USING SERIES EXPANSION METHODS M. Vorechovskˇ y´ 1 Summary: A practical framework for generating cross correlated fields with a specified marginal distribution function, an autocorrelation function and cross cor- relation coefficients is presented in the paper. The approach relies on well known series expansion methods for simulation of a Gaussian random field. The proposed method requires all cross correlated fields over the domain to share an identical au- tocorrelation function and the cross correlation structure between each pair of sim- ulated fields to be simply defined by a cross correlation coefficient. Such relations result in specific properties of eigenvectors of covariance matrices of discretized field over the domain. These properties are used to decompose the eigenproblem which must normally be solved in computing the series expansion into two smaller eigenproblems. Such a decomposition represents a significant reduction of compu- tational effort. Non-Gaussian components of a multivariate random field are proposed to be sim- ulated via memoryless transformation of underlying Gaussian random fields for which the Nataf model is employed to modify the correlation structure. In this method, the autocorrelation structure of each field is fulfilled exactly while the cross correlation is only approximated. The associated errors can be computed before performing simulations and it is shown that the errors happen especially in the cross correlation between distant points and that they are negligibly small in practical situations. 1. Introduction The random nature of many features of physical events is widely recognized both in industry and by researchers. -
Integrated Reliable and Robust Design
Scholars' Mine Masters Theses Student Theses and Dissertations Spring 2011 Integrated reliable and robust design Gowrishankar Ravichandran Follow this and additional works at: https://scholarsmine.mst.edu/masters_theses Part of the Mechanical Engineering Commons Department: Recommended Citation Ravichandran, Gowrishankar, "Integrated reliable and robust design" (2011). Masters Theses. 4860. https://scholarsmine.mst.edu/masters_theses/4860 This thesis is brought to you by Scholars' Mine, a service of the Missouri S&T Library and Learning Resources. This work is protected by U. S. Copyright Law. Unauthorized use including reproduction for redistribution requires the permission of the copyright holder. For more information, please contact [email protected]. INTEGRATED RELIABLE AND ROBUST DESIGN by GOWRISHANKAR RAVICHANDRAN A THESIS Presented to the Faculty of the Graduate School of the MISSOURI UNIVERSITY OF SCIENCE AND TECHNOLOGY In Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE IN MECHANICAL ENGINEERING 2011 Approved by Xiaoping Du, Advisor Arindam Banerjee Shun Takai iii ABSTRACT The objective of this research is to develop an integrated design methodology for reliability and robustness. Reliability-based design (RBD) and robust design (RD) are important to obtain optimal design characterized by low probability of failure and minimum performance variations respectively. But performing both RBD and RD in a product design may be conflicting and time consuming. An integrated design model is needed to achieve both reliability and robustness simultaneously. The purpose of this thesis is to integrate reliability and robustness. To achieve this objective, we first study the general relationship between reliability and robustness. Then we perform a numerical study on the relationship between reliability and robustness, by combining the reliability based design, robust design, multi objective optimization and Taguchi’s quality loss function to formulate an integrated design model.