Durakbasa / Gençyilmaz / Gençyilmaz Digital Conversion on the Way to Industry 4.0

Selected Papers from ISPR2020, September 24-26, 2020 Online - Turkey
1. Auflage 2020
ISBN: 978-3-030-62784-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 1018 Seiten

Reihe: Lecture Notes in Mechanical Engineering

This book presents the proceedings from the International Symposium for Production Research 2020. The cross-disciplinary papers presented draw on research from academics and practitioners from industrial engineering, management engineering, operational research, and production/operational management. It explores topics including:

·         computer-aided manufacturing;

• Industry 4.0 applications;
• simulation and modeling
big data and analytics;
• flexible manufacturing systems;
• decision analysis
• quality management
industrial robotics in production systems
• information technologies in production management; and
• optimization techniques.

 

Presenting real-life applications, case studies, and mathematical models, this book is of interest to researchers, academics,and practitioners in the field of production and operation engineering.

Zielgruppe

Research

Autoren/Hrsg.

Durakbasa, Numan M.

Gençyilmaz, M. Günes

Inhaltsverzeichnis

1;Foreword;6
2;Preface;7
3;Key Technology Roadmap In Production of Future – Industry 4.0;10
4;Organization;12
4.1;Editors;12
4.2;Co-editors;12
4.3;Honorary Chairs;12
4.4;Symposium Chairs;12
4.5;International Honorary Committee;13
4.6;Organizing Committee;13
4.7;This book is prepared for publishing by;13
4.8;Scientific Committee;13
4.9;Reviewers;16
5;Contents;18
6;Big Data and Analytics;27
7;A Hybrid Recommender System: Uniqueness of Choices by Using Machine Learning Technique;28
7.1;Abstract;28
7.2;1 Introduction;28
7.3;2 Statement of the Problem;29
7.3.1;2.1 Definitions;30
7.3.1.1;2.1.1 Vocabulary;30
7.3.1.2;2.1.2 Concepts;31
7.4;3 Proposed Recommender System Algorithm;31
7.5;4 Results and Discussions;34
7.6;5 Conclusions;37
7.7;References;37
8;IoT Based Real-World Emission Analysis of Motorcycles;39
8.1;Abstract;39
8.2;1 Introduction;40
8.3;2 IOT Connection of the Emission Measuring Device;41
8.4;3 Experimental Setup;43
8.5;4 Result of the Emission Monitoring;44
8.6;5 Conclusion;47
8.7;Acknowledgement;48
8.8;References;48
9;Decision Making;49
10;Using Best Worst Method for Location Selection of Piezoelectric Tiles;50
10.1;Abstract;50
10.2;1 Introduction;50
10.3;2 Best Worst Method as a Novel Multi-Criteriia Decision Making;51
10.4;3 The Proposed Methodology;52
10.4.1;3.1 Determination of the Criteria Set;52
10.4.2;3.2 Computation of Weights and Application Results;54
10.5;4 Conclusions;56
10.6;References;57
11;Facility and Capacity Management;58
12;Site Selection for a Training Centre Focused on Industry 4.0 by Using DEMATEL and COPRAS;59
12.1;Abstract;59
12.2;1 Introduction;60
12.3;2 Brief Description About the Digital Transformation Training and Practice Center;61
12.4;3 Site Selection for the Digital Transformation Training and Practice Center;63
12.4.1;3.1 DEMATEL as the Decision-Making Technique and Determining the Criteria to Be Used in Site Selection;64
12.4.2;3.2 COPRAS as the Decision-Making Technique and Evaluation of Site Selection Alternatives;67
12.5;4 Conclusion;70
12.6;Acknowledgement;71
12.7;References;71
13;Fuzzy Logic;73
14;Facility Location for Unmanned Aerial Vehicle Base Stations to Provide Uninterrupted Mobile Communication After Earthquakes;74
14.1;Abstract;74
14.2;1 Introduction;74
14.3;2 Weber Problem;76
14.4;3 Methodology;77
14.4.1;3.1 Determination of Distance in Probabilistic Methods;77
14.4.2;3.2 Determination of Demand in Probabilistic Methods;78
14.4.3;3.3 Fuzzy C-Means;78
14.4.4;3.4 Fuzzy C-Means – Center of Gravity (FCM– COG);79
14.5;4 Case Study;80
14.6;5 Results;80
14.7;6 Conclusion;81
14.8;References;81
15;Healthcare Systems and Management;83
16;A Guide Application in Case of Emergency Health: A Case of Turkey;84
16.1;Abstract;84
16.2;1 Introduction;84
16.3;2 Literature Review;85
16.3.1;2.1 World Healthcare System;85
16.3.2;2.2 Canadian Healthcare System;86
16.3.3;2.3 Turkish Healthcare System;88
16.4;3 Methodology;90
16.4.1;3.1 Turkey’s Mobile Health Application;90
16.4.2;3.2 Needs Analysis;90
16.4.3;3.3 Survey Questions and Analysis;91
16.5;4 Application Execution;93
16.5.1;4.1 Testing Process;94
16.6;5 Conclusion;95
16.7;References;95
17;Parametric Design and Modeling of 3D Printed Prosthetic Finger;99
17.1;Abstract;99
17.2;1 Introduction;99
17.3;2 Design of the Model;100
17.3.1;2.1 Mechanical Design;100
17.3.2;2.2 Parametric Design;103
17.3.3;2.3 Assembling Mechanism;105
17.4;3 Analysis and Results;106
17.5;4 Conclusion;108
17.6;References;108
18;Industrial Applications;110
19;Conceptual Design and Fluid Structure Interaction Analysis of a Solar Powered High-Altitude Pseudo-Satellite (HAPS) UAV Wing Model;111
19.1;Abstract;111
19.2;1 Introduction;111
19.3;2 Competitive Study;113
19.4;3 Wing Loading Estimation;114
19.5;4 Airfoil and Wing Geometry Selection;115
19.5.1;4.1 Airfoil Selection;115
19.5.2;4.2 Wing Geometry;116
19.6;5 Fluid Structure Interaction Analysis;118
19.6.1;5.1 Wing Model;118
19.6.2;5.2 Simulation and Analysis of the Wing Flow Field;119
19.6.3;5.3 Structural Analysis;121
19.7;6 Conclusions;122
19.8;Acknowledgment;122
19.9;References;122
20;Design and Development of Drum Granulator;124
20.1;Abstract;124
20.2;1 Introduction;124
20.3;2 Material and Method;125
20.3.1;2.1 Material;125
20.3.2;2.2 Method;125
20.3.3;2.3 Testing of the Drum Granulator;128
20.4;3 Results and Discussion;130
20.4.1;3.1 Design Process Results;130
20.4.2;3.2 Analysis Process Results;130
20.5;4 Conclusion;131
20.6;References;132
21;Forecasting Electricity Generation and Shares by Energy Resources by Time Series Analysis: A Case-Study of Turkey;133
21.1;Abstract;133
21.2;1 Introduction;133
21.3;2 Literature Review;134
21.4;3 Methodology and Modelling;135
21.5;4 Conclusion;138
21.6;References;138
22;Fused Filament Fabrication of Ceramic Components for Home Use;139
22.1;Abstract;139
22.2;1 Introduction;140
22.2.1;1.1 Objective and Research Question;141
22.2.2;1.2 Relevance of the Question;141
22.2.3;1.3 Methods;142
22.3;2 Fused Filament Fabrication;142
22.3.1;2.1 Process;142
22.3.2;2.2 Extrusion Methods;143
22.3.3;2.3 Ceramics;143
22.3.4;2.4 Binder;143
22.3.5;2.5 Debinding;144
22.3.6;2.6 Sintering;144
22.3.7;2.7 Parameters;145
22.3.8;2.8 Known Problem Areas in the Process;145
22.4;3 Market Situation;146
22.4.1;3.1 Filaments;146
22.4.2;3.2 Industrial Providers;147
22.5;4 Experimental;148
22.5.1;4.1 Print;148
22.5.2;4.2 Debinding;149
22.5.3;4.3 Sintering;150
22.5.4;4.4 Results;150
22.6;5 Discussion;151
22.7;6 Conclusions;153
22.8;References;153
23;Fused Filament Fabrication of Metallic Components for Semi-professional and Home Use;158
23.1;Abstract;158
23.2;1 Introduction;158
23.3;2 Methods;160
23.4;3 Theory;160
23.5;4 Empirical Market Research;161
23.6;5 Experimental;162
23.7;6 Discussion;165
23.8;References;165
24;Increasing of Stud Welding Efficiency in the Body Shop;168
24.1;Abstract;168
24.2;1 Description of the Used Stud Welding Technologies;168
24.2.1;1.1 Arc Welding of Bolts with Stroke;169
24.2.2;1.2 Point-Contact Welding of Studs;170
24.2.3;1.3 Welding of Studs in a Magnetic Field;170
24.3;2 Automation and Robotization of the Process;171
24.4;3 Solution of a Part of the Welding Line Using the Process Simulate Software;172
24.4.1;3.1 Description of the Welding Line;172
24.4.2;3.2 Dynamic Simulation;173
24.4.3;3.3 Setting the Kinematics of the Line Parts;175
24.4.4;3.4 Solution Simulation;176
24.4.5;3.5 Design of Welding Line Optimization;177
24.5;4 Conclusions;178
24.6;Acknowledgment;178
24.7;References;178
25;Measurements of a Finished Garment Using 3D Laser Image Processing;180
25.1;Abstract;180
25.2;1 Introduction;180
25.3;2 Related Works;181
25.4;3 Measurement Strategy;182
25.4.1;3.1 Key Aspects of Quality for the Customer (https://www.inspection-for-industry.com/finished-goods-inspection.html) (2020);182
25.4.2;3.2 Surface Form;182
25.5;4 Edge Detection;183
25.5.1;4.1 Main Steps in Edge Detection;184
25.5.2;4.2 Image Smoothing;185
25.5.3;4.3 Edges and Boundaries;186
25.5.4;4.4 Image Segmentation Using Edge Detection;186
25.5.5;4.5 Using the Hough Transform;187
25.5.6;4.6 Segmentation Methods;188
25.6;5 Measurement of Jacket and Conclusion;189
25.6.1;5.1 Measurement by Using 3D Laser Scanner-Non-contact Blue Laser;189
25.6.2;5.2 Measurement Through Two-Dimensional Image;190
25.7;6 Conclusion;191
25.8;References;192
26;Porosity Measurement by X – Ray Computed Tomography: Different Porosity Analysis Application;193
26.1;Abstract;193
26.2;1 Introduction;193
26.3;2 Experimental Investigation;197
26.4;3 Conclusions;202
26.5;Acknowledgment;203
26.6;References;203
27;Industrial Robotics in Production Systems and Industrial Engineering;204
28;Accuracy Improvement and Process Flow Adaption for Robot Machining;205
28.1;Abstract;205
28.2;1 Introduction;205
28.3;2 Industrial Robots and CNC Machine Tools;206
28.4;3 Calibration and Offline Compensation;208
28.4.1;3.1 Calibration;208
28.4.2;3.2 Offline Compensation;209
28.5;4 Hardware and Software Adaption;212
28.5.1;4.1 Existing Station and Production Process;212
28.5.2;4.2 Enhancements for Automated Process Environment;213
28.6;5 Conclusions;214
28.7;References;214
29;Artificial Neural Networks Based Place Categorization;217
29.1;Abstract;217
29.2;1 Introduction;217
29.3;2 Supervised Learning;218
29.4;3 Convolutional Neural Networks;218
29.5;4 Implemented Algorithms;220
29.5.1;4.1 Naïve Bayes Filter;220
29.5.2;4.2 Multinomial Logistic Regression;220
29.5.3;4.3 Support Vector Machines;221
29.6;5 Results and Discussion;222
29.7;6 Conclusion;223
29.8;References;224
30;Logic Control of an Industrial Automation Cell with ROS as Part of SMEs and Industry 4.0 Interconnection;226
30.1;Abstract;226
30.2;1 Introduction;227
30.2.1;1.1 State of the Art;227
30.2.2;1.2 Related Work;228
30.2.3;1.3 Problem Definition;228
30.3;2 Open Source Process Logic;229
30.3.1;2.1 Basic Concepts;229
30.3.2;2.2 Robot Modeling;230
30.3.3;2.3 Motion Planning;232
30.4;3 Automation Cell;233
30.4.1;3.1 Components of Process Control;233
30.4.2;3.2 Robot Arm System;233
30.4.3;3.3 Model/Visualization/Control GUI;234
30.4.4;3.4 Software Controller/Simulation/Robot Controller;235
30.5;4 Conclusions;236
30.6;5 Next Steps;236
30.7;References;237
31;Robot Retrofitting by Using LinuxCNC Complemented with Arduino/RaspberryPI;238
31.1;Abstract;238
31.2;1 Introduction;239
31.2.1;1.1 The Industrial Automation Need, Yesterday, Today, Tomorrow;239
31.2.2;1.2 Yesterday, the Puma560 Milestone;240
31.2.3;1.3 The “Engelberger Robotics Award”;240
31.2.4;1.4 Today Industrie 4.0;240
31.2.5;1.5 Tomorrow, Automation Robotic Autonomation;241
31.3;2 LinuxCNC;241
31.3.1;2.1 LinuxCNC History and Strong Current Use;241
31.3.2;2.2 LinuxCNC Main Idea and Possibilities Foreseen in the Original Concept;241
31.3.3;2.3 Components;242
31.3.4;2.4 User Interface;242
31.3.5;2.5 Hardware Abstraction Layer;243
31.3.6;2.6 HAL Concepts (LinuxCNC, 2020);243
31.3.7;2.7 HAL Tools;243
31.3.8;2.8 Examining the HAL;244
31.3.9;2.9 Loading Components;244
31.3.10;2.10 Robot Geometry: GENSERKINS;245
31.3.11;2.11 Planning Movement: MOTMOD;245
31.3.12;2.12 Controlling the Step Motors: STEPGEN;245
31.3.13;2.13 Bringing Signals to the Real World: HAL_PARPORT;246
31.3.14;2.14 Other Component, DDT;247
31.3.15;2.15 A Real World Controller;247
31.4;3 Arduino/Raspberry PI, (and Other Similar Hardware);248
31.5;4 Modern Motors, Design and Control of Special Brushless Motors;249
31.6;5 Advantages of Quickly Switching from: The Real World to the Virtual World (Emulator);249
31.7;6 Conclusions;250
31.8;7 Next Steps;251
31.9;References;251
32;Parameter Optimization for the 3D Print of Thermo-Plastic Pellets with an Industrial Robot;252
32.1;Abstract;252
32.2;1 Introduction;253
32.3;2 Problem Description;253
32.4;3 Materials and Methods;254
32.5;4 Practical Realization;255
32.6;5 Print Results;256
32.7;6 Alternative Pellet Extruders;257
32.8;7 Design of New Pellet Extruder;259
32.9;8 Conclusion;261
32.10;References;262
33;Industry 4.0 Applications;264
34;A Comparative Sectoral Analysis of Industry 4.0 Readiness Levels of Turkish SMEs;265
34.1;Abstract;265
34.2;1 Introduction;266
34.3;2 Methodology;268
34.4;3 Implementation and Results;268
34.5;4 Conclusions;275
34.6;Acknowledgment;276
34.7;References;276
35;A Decision Support Tool for Classification of Turkish SMEs’ Industry 4.0 Score Levels;278
35.1;Abstract;278
35.2;1 Introduction;279
35.3;2 Methodology;280
35.3.1;2.1 Data Classification;280
35.3.2;2.2 Performance Evaluation;281
35.3.3;2.3 Estimation Methodologies;282
35.4;3 Implementation and Results;283
35.4.1;3.1 Data Description and Preprocessing;283
35.4.2;3.2 Hyperparameter Tuning;284
35.5;4 Results;285
35.5.1;4.1 Decision Support Tool;285
35.6;5 Conclusions;286
35.7;Acknowledgment;286
35.8;Appendix-I;287
35.9;Appendix-II;287
35.10;Appendix-III;288
35.11;Appendix-IV;288
35.12;Appendix-V;289
35.13;References;289
36;Adaptation of CNC Machine Tools in Educational Center That Matches the Concept of Industry 4.0;291
36.1;Abstract;291
36.2;1 Introduction;291
36.3;2 Problem Analysis;292
36.4;3 Case Study;297
36.5;4 Conclusions;301
36.6;References;301
37;Digital Maturity Assessment Model for Smart Agriculture;303
37.1;Abstract;303
37.2;1 Introduction;303
37.3;2 Smart Agriculture;305
37.4;3 Methodology;305
37.4.1;3.1 Determination of Criteria Set;306
37.4.2;3.2 Determination of Weights;309
37.4.3;3.3 Application;312
37.5;4 Conclusions;313
37.6;References;314
38;Do We Need Synchronization of the Human and Robotics to Make Industry 5.0 a Success Story?;316
38.1;Abstract;316
38.2;1 Introduction;316
38.3;2 Background;317
38.3.1;2.1 Automation of Work;318
38.3.2;2.2 Collaborative Robots (Cobots);319
38.3.3;2.3 Robocollaborators (Coboters);320
38.4;3 Systems and Theories;320
38.4.1;3.1 Socio-Technical Methodology;320
38.4.2;3.2 A Design Method: Reinventing Jobs;321
38.4.3;3.3 Synchronising Cobots and Coboters;323
38.5;4 An Industrial Proposal;323
38.6;5 Conclusions;324
38.7;References;325
39;Evaluation of the Challenges of Companies in Industry 4.0 Transformation by GRA Method;326
39.1;Abstract;326
39.2;1 Introduction;326
39.3;2 Challenges of Companies in Industry 4.0 Transformation;327
39.4;3 Methodology;331
39.5;4 Data Analysis;333
39.6;5 Conclusions;335
39.7;References;336
40;Industry 4.0 in Educational Process;338
40.1;Abstract;338
40.2;1 Introduction;338
40.3;2 Industry Requirements;339
40.3.1;2.1 Requirements for the Area of Production Systems;340
40.3.2;2.2 Qualification and Skills for Industry;341
40.4;3 Implementation Phase;342
40.4.1;3.1 Education in Production Systems;342
40.4.2;3.2 Educational Concept;343
40.5;4 Conclusions;345
40.6;Acknowledgment;345
40.7;References;345
41;Industry 4.0 vs. Society 5.0;347
41.1;Abstract;347
41.2;1 Introduction;347
41.3;2 Industry 4.0 and Society 5.0 Joint Parameters;348
41.3.1;2.1 Big Data;348
41.3.2;2.2 Artificial Intelligence;349
41.3.3;2.3 Internet of Things (IoT);350
41.3.4;2.4 Cloud Computing;350
41.3.5;2.5 Human;351
41.4;3 Industry 4.0;351
41.5;4 Society 5.0;353
41.6;5 Industry 4.0 vs. Society 5.0;354
41.7;6 Conclusions and Related Work;356
41.8;References;357
42;Intelligent Design and Advanced Precision Metrology on the Geometrical Structure of Medical Needles Based on GPS and ISO Standards;360
42.1;Abstract;360
42.2;1 Introduction;361
42.3;2 Methods and Theoretical Parts;362
42.3.1;2.1 Purpose of Using Glass Pre-fillable Syringe with Needle G27;362
42.3.2;2.2 Injection Application Technique of Needle G27 of Glass Pre-fillable Syringe;363
42.3.3;2.3 Functional Requirements and Specifications;363
42.3.4;2.4 Production Process and Geometrical Definition;363
42.3.5;2.5 Geometrical Product Specifications;365
42.3.6;2.6 Micro and Macro Geometrical Assessment Through Measurement Device;367
42.4;3 Results;368
42.5;4 Conclusion and Prospect;374
42.6;References;375
43;Social and Ethical Aspects of Automation;377
43.1;Abstract;377
43.2;1 Introduction;377
43.3;2 Automation;378
43.3.1;2.1 Production 4.(5).0;378
43.3.2;2.2 Humans in Manufacturing Automation;380
43.4;3 Ethics;381
43.5;4 Social Aspects;382
43.5.1;4.1 Robocollaborators;382
43.5.2;4.2 Legal Questions;383
43.6;5 Summary and Outlook;385
43.7;References;386
44;Social Transformation - Industry 4.0;387
44.1;Abstract;387
44.2;1 Industry 4.0;387
44.3;2 The Door to Change;388
44.4;3 How Prepared Are We for Change?;390
44.4.1;3.1 Technological Knowledge Level;391
44.4.2;3.2 Technological Development;391
44.4.3;3.3 Digital Transformation Agility;391
44.5;4 Society 5.0;393
44.6;5 Project Management;394
44.7;6 The Effects of Change on Project Management;394
44.8;7 Conclusion and Evaluation;395
44.9;References;396
45;Strategic Model Proposal Related to IoT Applications in Disaster Management;397
45.1;Abstract;397
45.2;1 Introduction;397
45.3;2 Disaster Management;398
45.4;3 IoT;398
45.5;4 Strategic Model Proposal to Disaster Management with IoT;399
45.6;5 Conclusions;401
45.7;References;402
46;Usage and Applications of the Swarm Robotics Concept at Industrial Level;403
46.1;Abstract;403
46.2;1 Introduction;403
46.3;2 Swarm Robotics;404
46.4;3 Definition of the Problem;405
46.5;4 Related Works;405
46.6;5 Method;405
46.7;6 Application;407
46.8;7 Conclusion;410
46.9;Acknowledgments;411
46.10;References;411
47;Information Management;412
48;Design of a Database Management System for Movie Recommendation Related to the History of Industrial Engineering for Courses;413
48.1;Abstract;413
48.2;1 Introduction;413
48.3;2 Using Movies as Educational Tools;415
48.4;3 Database Management and Suggestion Systems Developed for Movies;416
48.5;4 Method;416
48.5.1;4.1 A Database Management System that Associates Education Topics with Movies and Suggests a Course;417
48.5.2;4.2 The Database Is Created with the Determined Keywords and/or Terms;417
48.5.3;4.3 Associating Courses, Terms, and Films by Establishing a Database;417
48.5.4;4.4 Connecting Database and C#;417
48.5.5;4.5 Building the Application Structure;418
48.6;5 Application;418
48.6.1;5.1 SQLite;418
48.7;6 Conclusions;420
48.8;References;423
49;Process Mining Research in Management Science and Engineering Fields: The Period of 2010–2019;425
49.1;Abstract;425
49.2;1 Introduction;425
49.3;2 Literature Review;426
49.4;3 Methodology;428
49.4.1;3.1 Aim of the Study and Research Questions;428
49.4.2;3.2 Bibliometric Study and Data Collection;428
49.5;4 Results;429
49.5.1;4.1 Main Findings of Descriptive Publication Results;429
49.5.2;4.2 Distribution of Articles by Years;430
49.5.3;4.3 Journal and Source Frequency and Productivity;430
49.5.4;4.4 Author’s Productivity;431
49.5.5;4.5 Organizations and Countries Productivity;431
49.5.6;4.6 Citation Results;433
49.6;5 Discussions and Conclusions;433
49.7;References;435
50;Lean Production;438
51;Waiting as Waste in Lean Production Processes;439
51.1;Abstract;439
51.2;1 Introduction;439
51.3;2 Model Construction;441
51.3.1;2.1 Scheduling and Waiting;441
51.3.2;2.2 Effects of Reduction of Waiting Time;442
51.4;3 Discussion – Case Study;443
51.5;4 Summary and Conclusions;446
51.6;References;446
52;Logistics Management;448
53;A Critical Review of Quality Function Deployment (QFD) Tool Through Logistics Centre Development Projects;449
53.1;Abstract;449
53.2;1 Introduction;449
53.2.1;1.1 What Is the Aim of This Symposium Paper?;449
53.2.2;1.2 How Do We Describe a Logistics Centre?;450
53.2.3;1.3 What Is the Contribution of This Study in Regards with a Logistics Centre Development Project?;450
53.3;2 Review and Assessment Framework for QFD Processes;451
53.3.1;2.1 Data Gathering: Converting VoC into Input for QFD Processes;451
53.3.2;2.2 Relativeness and Connectivity Integrity of QFD Inputs;453
53.3.3;2.3 Priority Check and Ranking the QFD Inputs;454
53.3.4;2.4 Improving the QFD Processes;455
53.3.5;2.5 Interpretation of QFD Process Outputs;456
53.3.6;2.6 Maximizing the Benefits of QFD While Get Rid of the Means that Hinder the Ultimate Success;457
53.3.7;2.7 How We Have Applied the Phases of QFD Methodology in a Logistics Centre Development Project?;458
53.4;3 Conclusions;459
53.5;References;459
54;Two-Phase Fuzzy C-Means and Genetic Algorithm for Food Distribution;461
54.1;Abstract;461
54.2;1 Introduction;461
54.3;2 Problem Definition;463
54.4;3 Proposed Algorithm;463
54.5;4 Results;465
54.6;5 Conclusion;467
54.7;References;467
55;Optimization;469
56;Modelling and Optimization of Dissimilar Welding Between 304L and HSLA-X70 Using Response Surface Methodology;470
56.1;Abstract;470
56.2;1 Introduction;470
56.3;2 Design of Experiments;471
56.4;3 Results and Discussion;473
56.4.1;3.1 Statistical Analysis;473
56.4.2;3.2 Regression Equations;474
56.4.3;3.3 Effect of Welding Parameters on Surface Response Factors;475
56.5;4 Optimization of Welding Conditions;475
56.6;5 Conclusions;478
56.7;References;478
57;Proposing a Pre-emptive Resource Constrained Project Scheduling Problem (PRCPSP) Model to Optimize Manpower and Project Delivery Time (A Case Study);480
57.1;Abstract;480
57.2;1 Introduction and Literature Review;480
57.3;2 Problem Definition;481
57.4;3 Numerical Results and Case Study;485
57.5;4 Conclusions and Further Research;487
57.6;References;487
58;Process Management;488
59;Improvements in Manufacturing Processes by Measurement and Evaluation Studies According to the Quality Management System Standard in Automotive Industry;489
59.1;Abstract;489
59.2;1 Introduction;490
59.3;2 Measurement Systems Analysis (MSA);490
59.4;3 Application of Quantitative MSA;491
59.5;4 Application of Qualitative MSA;494
59.6;5 Conclusions;497
59.7;References;497
60;Improving Business Processes of Human Resources Departments in Turkish Technic Inc.;499
60.1;Abstract;499
60.2;1 Introduction;499
60.3;2 L?terature Rev?ew;500
60.4;3 Methodology;503
60.4.1;3.1 Constraints;503
60.4.2;3.2 Analysis and Research;503
60.4.3;3.3 Main Design;507
60.5;4 Conclus?ons;508
60.6;References;509
61;Improving Manufacturing Process of Mobile Recorder;510
61.1;Abstract;510
61.2;1 Introduction;510
61.3;2 Material and Method;512
61.3.1;2.1 Design of the Interior and Exterior Case;512
61.3.2;2.2 Steps for the Production of Conventional Mobile Recorder;512
61.3.3;2.3 Production of Planned Mobile Recorder;513
61.4;3 Results and Discussion;514
61.5;4 Conclusions;517
61.6;Acknowledgement;517
61.7;References;517
62;Manufacturing Process Development for Thin Film Filaments as a New Product;519
62.1;Abstract;519
62.2;1 Introduction;519
62.3;2 Experimental Method;522
62.4;3 Results;523
62.5;4 Conclusion;525
62.6;References;526
63;Modelling of the High-Chromium Cast Iron Surface Roughness;529
63.1;Abstract;529
63.2;1 Introduction;529
63.3;2 The Experiment;531
63.4;3 Model Implementation and Discussion;535
63.5;4 Conclusion;538
63.6;Acknowledgment;539
63.7;References;539
64;Productivity and Performance Management;541
65;A System Dynamics Model for Long-Term Performance Monitoring of Projects Related to Oil Production in Iran;542
65.1;Abstract;542
65.2;1 Introduction and Literature Review;542
65.3;2 Problem;543
65.4;3 Model;543
65.4.1;3.1 Variables and Reference Trends;544
65.4.2;3.2 Stock-Flow Diagram;546
65.5;4 Model Validation;547
65.6;5 Result and Conclusion;548
65.7;References;550
66;An SME Examination on the Effect of Transition to Automation Systems on Production Performance;551
66.1;Abstract;551
66.2;1 Introduction;552
66.3;2 Production Performance;553
66.4;3 Automation System;553
66.5;4 Implementation;554
66.5.1;4.1 Problems Experienced in Transition to Automation Systems;555
66.5.2;4.2 Effect of Automation System on Production Performance;557
66.6;5 Conclusion and Recommendations;560
66.7;Acknowledgements;561
66.8;References;561
67;Performance Evaluation in the Firms of Turkish Textile Sector;563
67.1;Abstract;563
67.2;1 Introduction;563
67.3;2 Literature Review;564
67.4;3 Material and Method;565
67.5;4 Results and Discussion;566
67.6;5 Conclusion;571
67.7;References;572
68;Some Universities Performance Evaluation of Entrepreneurship and Innovation in Turkey with Multiple Criteria Decision Making Methods;574
68.1;Abstract;574
68.2;1 Introduction;575
68.3;2 Literature Research;577
68.4;3 Purpose of the Research;579
68.4.1;3.1 Methodology of the Study;579
68.4.2;3.2 Data Used in the Research;580
68.4.3;3.3 Evaluation of GYU Performance with Promethee GAIA Method;580
68.5;4 Conclusions and Suggestions;585
68.6;References;587
69;Turkey and Some EU Countries’ Economic Performance Analysis with Multi-criteria Decision Making Methods: Promethee GAIA Application;589
69.1;Abstract;589
69.2;1 Introduction;590
69.3;2 Literature Research;591
69.4;3 Methodology of the Research;595
69.4.1;3.1 Purpose of the Research;595
69.4.2;3.2 Data and Method;595
69.4.3;3.3 Evaluation of Economic Performance with PROMETHEE Method;596
69.4.4;3.4 Comparison of Economic Performance of Countries;599
69.5;4 Conclusion and Comments;600
69.6;References;601
70;Warehouse Planning for Maximum Area Efficiency in the White Goods Sector;603
70.1;Abstract;603
70.2;1 Introduction;603
70.3;2 Literature Review;604
70.4;3 Application;605
70.5;4 Results;607
70.6;5 Future Studies and Suggestions;608
70.7;References;608
71;Quality Management;609
72;Geometric Tolerancing Analysis of Multi-material Components (MMCs) Obtained by Industrial X-Ray Computed Tomography;610
72.1;Abstract;610
72.2;1 Introduction;610
72.3;2 Literature Review;611
72.4;3 Materials and Methods;611
72.5;4 Results and Discussions;612
72.6;5 Conclusions;615
72.7;Acknowledgements;615
72.8;References;615
73;Intelligent Test Automation for Improved Software Quality Assurance;617
73.1;Abstract;617
73.2;1 Introduction: Quality Assurance and Testing;617
73.3;2 Software Testing;618
73.4;3 Automation: Intelligent Testing;619
73.5;4 Current Challenges in Test Automation;620
73.6;5 QiTASC Test Automation: Smart Testing;621
73.6.1;5.1 Why intaQt Automation?;621
73.6.2;5.2 Combining QiTASC Products to Achieve High Levels of Automation;623
73.6.3;5.3 Complex and Multi-context Systems Can Easily Be Automated by intaQt;625
73.6.4;5.4 Further Automation Possibilities in the Agenda;626
73.7;6 Conclusion;626
73.8;References;626
74;The Role of Product Perceived Quality in Building Customer Behavioral Loyalty Across Retail Channels;628
74.1;Abstract;628
74.2;1 Introduction;628
74.3;2 Theoretical Background on Customer Loyalty, Role of Product Quality and Other Factors;630
74.3.1;2.1 Customer Loyalty in Omnichannel Retail;630
74.3.2;2.2 Product Quality and Loyalty;631
74.4;3 Research Methodology;632
74.4.1;3.1 Research Framework and Questions;632
74.4.2;3.2 Research Method and Data;634
74.5;4 Results;635
74.5.1;4.1 Factors of Loyalty in Offline Channel;636
74.5.2;4.2 Factors of Loyalty in Online Channel;638
74.5.3;4.3 Summary of Results and Managerial Implications Concerning Product Quality Role in Building Behavioral Loyalty;638
74.6;5 Conclusions and Discussion;640
74.7;References;641
75;R&D and Technology Management;644
76;Innovation Efficiency in Automotive Industry: The Case of Turkey;645
76.1;Abstract;645
76.2;1 Introduction;645
76.3;2 Literature Review;646
76.4;3 Methodology;647
76.4.1;3.1 CCR Model Results;650
76.4.2;3.2 BCC Model Results;654
76.5;4 Conclusions and Recommendations;658
76.6;References;659
77;Overview of Technology Commercialization Options in Romania;660
77.1;Abstract;660
77.2;1 Introduction;660
77.3;2 Context and Methodology;661
77.4;3 Implementation of the Investigation Methodology and Main Results;662
77.5;4 Discussion of Outcomes and Implication;664
77.6;5 Conclusions;666
77.7;References;666
78;Risk Analysis and Management;667
79;Physical Asset Risk Management: A Case Study from an Asset-Intensive Organization;668
79.1;Abstract;668
79.2;1 Introduction;668
79.3;2 Literature Review;669
79.4;3 Physical Asset Risk Management Process;669
79.4.1;3.1 Determination of Physical Assets’ Risks;670
79.4.2;3.2 Determination of Critical Physical Assets’ Risks;670
79.4.3;3.3 Select RTPs;672
79.5;4 Case Study;674
79.5.1;4.1 Determination of PP’s Physical Assets’ Risks;675
79.5.2;4.2 Determination of PP’s Critical Risks Related to Physical Assets;675
79.5.3;4.3 Select RTPs for PP’s Physical Assets;677
79.6;5 Conclusions;678
79.7;References;678
80;Risk Analysis Application for a Medical Device Manufacturer;680
80.1;Abstract;680
80.2;1 Introduction and Purpose;680
80.3;2 Basic Concepts;681
80.4;3 Risk Management Process;682
80.5;4 Risk Analysis Methods;682
80.6;5 A Case Study on Risk Management Process;684
80.7;6 Conclusion;690
80.8;References;690
81;Scheduling;691
82;Hybrid Flowshop Scheduling Problem at DrPaste;692
82.1;Abstract;692
82.2;1 Introduction;692
82.3;2 NP-Hardness of the Problem;694
82.4;3 Production Environment;694
82.5;4 Genetic Algorithm;697
82.6;5 Actual Size Problem Data;700
82.7;6 Small Size Problem;700
82.8;7 Parameter Tuning;701
82.9;8 Design of User Interface;702
82.10;9 Conclusion;705
82.11;References;705
83;Service System Management;707
84;Effect of Gamification Applications on Individual Performance: Air Transportation Application;708
84.1;Abstract;708
84.2;1 Introduction;708
84.3;2 Gamification Background;709
84.4;3 Proposed Model and Results;710
84.5;4 Conclusions and Recommendations;714
84.6;References;715
85;Simulation and Modelling;717
86;A Brief General Industrial Virtual Reality Applications Overview Including a Simple Factory VR Simulation;718
86.1;Abstract;718
86.2;1 Introduction;718
86.2.1;1.1 Necessity of VR According to Industry 4.0;718
86.2.2;1.2 Digital Twinning for the Visualization Process;719
86.3;2 A Brief Literature Review for Applications of VR;720
86.3.1;2.1 Industrial VR Applications;720
86.3.2;2.2 VR Applications in Industrial Education;722
86.3.3;2.3 Other General VR Applications;724
86.4;3 Experimental Procedure and Results of VR Workshop Simulation;725
86.5;4 Conclusions;727
86.6;References;727
87;Investigation of the Efficiency of Vibration-Assisted Nano-Grinding with Molecular Dynamics;731
87.1;Abstract;731
87.2;1 Introduction;731
87.3;2 Methodology;734
87.4;3 Results and Discussion;736
87.5;4 Conclusions;740
87.6;References;740
88;Supply Chain Management;743
89;A New Approach to Location Routing Problem: Capacitated Periodic Location Routing Problem with Inventory;744
89.1;Abstract;744
89.2;1 Introduction;744
89.3;2 Literature;746
89.4;3 Problem Definition;748
89.5;4 Simulated Annealing for the CPRLPI;752
89.6;5 Discussion;755
89.7;6 Conclusion and Recommendations;757
89.8;Acknowledgment;757
89.9;References;757
90;Smart Manufacturing of Electric Vehicles;760
90.1;Abstract;760
90.2;1 Introduction;761
90.2.1;1.1 Mobility Needs and Trends;761
90.3;2 Microfactory Concept;762
90.3.1;2.1 Cleaner Energy Management;764
90.3.2;2.2 Sustainable Supply Chain Model for Microfactory Network;765
90.4;3 Conclusions;765
90.5;References;766
91;Capstone Projects;767
92;A Multi-sided and Multi-model Assembly Line Balancing Problem;768
92.1;Abstract;768
92.2;1 Introduction;768
92.3;2 Literature Review;770
92.4;3 Problem Formulat?on;771
92.5;4 Computational Results and Decision Support System;774
92.5.1;4.1 Verification;774
92.5.2;4.2 Validation and Improvements;774
92.5.3;4.3 Sensitivity Analysis;776
92.5.4;4.4 Decision Support System;778
92.6;5 Conclusion;779
92.7;Acknowledgments;779
92.8;References;780
93;A Parallel Machine Scheduling Problem for a Plastic Injection Company;781
93.1;Abstract;781
93.2;1 Introduction;781
93.3;2 Problem Definition;782
93.3.1;2.1 Current System Observations and Symptoms;782
93.3.2;2.2 Problem Definition;783
93.4;3 Literature Review;783
93.5;4 Problem Formulation;785
93.6;5 Solution Methodology;787
93.7;6 Decision Support System;789
93.8;7 Verification and Validation;791
93.9;8 Conclusions;792
93.10;Acknowledgment;793
93.11;References;793
94;A Single Machine Job Scheduling Problem with Sequence Dependent Setup Times;795
94.1;Abstract;795
94.2;1 Introduction;795
94.3;2 Problem Definition and Literature Review;796
94.4;3 Problem Formulation;797
94.5;4 Heuristic Algorithms;799
94.5.1;4.1 ATCS Rule Based Heuristic Algorithm;799
94.5.2;4.2 EDD, WEDD, SPT and WSPT Rule based Heuristic Algorithms;802
94.6;5 Computational Experiments;802
94.6.1;5.1 Comparison of Algorithms with Respect to the Optimal Results;803
94.6.2;5.2 Comparison of Algorithms with Time-Limited CPLEX;804
94.7;6 Decision Support System;805
94.8;7 Conclusion and Future Work;807
94.9;References;807
95;An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company;808
95.1;Abstract;808
95.2;1 Introduction;808
95.3;2 Problem Definition;809
95.3.1;2.1 Data Analysis;810
95.3.2;2.2 System Analysis;810
95.4;3 Literature Review;812
95.5;4 Solution Methodology;813
95.5.1;4.1 Mathematical Model;813
95.5.2;4.2 Heuristic Algorithm;815
95.6;5 Verification, Validation and Computational Results;818
95.6.1;5.1 Real Data;819
95.6.2;5.2 Hypothesis Testing;820
95.7;6 Conclusion;820
95.8;Acknowledgment;821
95.9;References;821
96;Analysis and Improvement of Employee Transportation System;822
96.1;Abstract;822
96.2;1 Introduction;822
96.3;2 Problem Definition;823
96.3.1;2.1 Current System and Symptoms of the Problem;823
96.3.2;2.2 Problem Definition;823
96.4;3 Literature Review;824
96.5;4 Problem Formulation;825
96.6;5 Solution Methodology;827
96.7;6 Computational Results;829
96.8;7 Conclusions;831
96.9;References;831
97;Container Demand Forecasting Using Machine Learning Methods: A Real Case Study from Turkey;833
97.1;Abstract;833
97.2;1 Introduction;833
97.3;2 Literature Review;834
97.4;3 Problem Definition;836
97.5;4 Methodology;837
97.5.1;4.1 Machine Learning;837
97.5.1.1;4.1.1 Artificial Neural Networks (ANN);837
97.5.1.2;4.1.2 Decision Trees;838
97.5.1.3;4.1.3 Decision Forest/Random Forest (RF);838
97.5.2;4.2 Linear Regression;838
97.5.3;4.3 Performance Metrics to Evaluate Forecasting Models;839
97.5.3.1;4.3.1 Mean Absolute Error (MAE);839
97.5.3.2;4.3.2 Root Mean Square Error (RMSE);839
97.5.3.3;4.3.3 Relative Absolute Error (RAE);839
97.5.3.4;4.3.4 Relative Squared Error (RSE);839
97.5.3.5;4.3.5 Coefficient of Determination (R2);840
97.6;5 Results;840
97.7;6 Conclusion;841
97.8;Acknowledgment;842
97.9;References;842
98;Customer Order Scheduling in Hybrid Flow Shop Manufacturing System;844
98.1;Abstract;844
98.2;1 Introduction;844
98.3;2 Problem Definition;845
98.4;3 Literature Review;846
98.5;4 Modeling and Solution Methodology;846
98.5.1;4.1 Limitations and Assumptions;846
98.5.2;4.2 Mathematical Model;847
98.5.3;4.3 Genetic Algorithm;849
98.6;5 Verification and Validation;850
98.7;6 Decision Support System and Computational Results;852
98.7.1;6.1 Decision Support System (DSS);852
98.7.2;6.2 Computational Results;854
98.8;7 Conclusions and Future Work;855
98.9;Acknowledgements;856
98.10;References;856
99;Development of Hydraulic Drive Railway Bearings Installation System;857
99.1;Abstract;857
99.2;1 Introduction;857
99.3;2 Material and Method;858
99.3.1;2.1 Material of Pipe of Hydraulic Cylinder and Mounting-Dismounting Fixtures;858
99.4;3 Method;859
99.5;4 Results and Discussion;861
99.5.1;4.1 Design of Hydraulic Drive Railway Bearings Installation System;861
99.5.2;4.2 Static Structural Analysis;862
99.5.3;4.3 Manufacturing;864
99.6;5 Conclusion;865
99.7;Acknowledgment;865
99.8;References;866
100;Improving the Operations in a Logistics Company: A Case Study in Turkey;867
100.1;Abstract;867
100.2;1 Introduction;867
100.3;2 Literature Review;868
100.4;3 QFD Methodology;870
100.5;4 Implementation of the Study;872
100.6;5 Discussions and Conclusion;876
100.7;References;877
101;Improving the Throughput of Pipe and Tube Production: A Case Study;879
101.1;Abstract;879
101.2;1 Introduction;879
101.3;2 Literature Review;880
101.4;3 Problem Formulation;881
101.5;4 Solution Methodology;883
101.6;5 Computational Results;885
101.6.1;5.1 WIP Study;885
101.6.2;5.2 Layout Optimization;886
101.7;6 Conclusion;889
101.8;Acknowledgment;890
101.9;References;890
102;Integrated Transportation and Packaging Problem Modeling and Application;891
102.1;Abstract;891
102.2;1 Introduction;891
102.3;2 Literature Review;892
102.4;3 Problem Formulation;893
102.5;4 Heuristic Algorithm;897
102.6;5 Computational Results;899
102.7;6 Decision Support System;900
102.8;7 Conclusion and Future Work;902
102.9;Acknowledgments;903
102.10;References;903
103;Lean Warehouse Application in a Meat Producer Company;905
103.1;Abstract;905
103.2;1 Introduction;905
103.3;2 Observations and System;906
103.4;3 Problem Definition;907
103.5;4 Literature Review;908
103.5.1;4.1 Lean Management;908
103.5.2;4.2 Value Stream Mapping;910
103.6;5 Methodology;910
103.6.1;5.1 Proposed Methodology: ABC Analysis;910
103.6.2;5.2 Current State Map;914
103.6.3;5.3 Future State Map;916
103.7;6 Conclusion;917
103.8;References;918
104;Location Optimization of Receivers for IoT- Based Infrastructures;921
104.1;Abstract;921
104.2;1 Introduction;921
104.3;2 Literature Review;923
104.4;3 Problem Formulation;924
104.4.1;3.1 Mathematical Modeling;925
104.5;4 Computational Results;930
104.6;5 Decision Support System;930
104.7;6 Conclusions;932
104.8;References;932
105;Makespan Minimization in Manufacturing Process of a Company;934
105.1;Abstract;934
105.2;1 Introduction;934
105.3;2 Literature Review;935
105.4;3 Methodology and Modelling;936
105.5;4 Result of the Mathematical Modeling;940
105.6;5 Conclusion;940
105.7;References;940
106;Multi Model Multiple Line Balancing Problem Modeling and Real-Life Application;942
106.1;Abstract;942
106.2;1 Introduction;942
106.3;2 Problem Definition;943
106.4;3 Literature Review;944
106.5;4 Solution Methodology;945
106.5.1;4.1 Assignment Algorithm;945
106.5.2;4.2 Mathematical Model;947
106.6;5 The Computational Results and Implementation;949
106.7;6 Decision Support System;950
106.8;7 Conclusion and Future Work;951
106.9;Acknowledgment;952
106.10;References;952
107;Quantitative Analysis of Stakeholder Perspective on the University-Industry-Government Collaboration in ?zmir, Turkey;954
107.1;Abstract;954
107.2;1 Introduction;954
107.3;2 Literature Review;955
107.4;3 Methodology;958
107.5;4 Analysis and Findings;960
107.6;5 Conclusions;963
107.7;Acknowledgment;963
107.8;References;963
108;Parcel Delivery Service Quality Assessment;966
108.1;Abstract;966
108.2;1 Introduction;966
108.3;2 Literature Review;967
108.4;3 Methodology;968
108.4.1;3.1 Description of the SERVQUAL Method;968
108.4.2;3.2 Description of the KANO Method;969
108.4.3;3.3 Survey Development;970
108.4.4;3.4 Participants;970
108.5;4 Findings;971
108.5.1;4.1 SERVQUAL Findings;971
108.5.2;4.2 Kano Findings;973
108.6;5 Conclusion;976
108.7;References;977
109;Production Scheduling at a Powder Coating Company;980
109.1;Abstract;980
109.2;1 Introduction;980
109.3;2 Problem Formulation and Solution Methodology;981
109.3.1;2.1 Mathematical Model;982
109.3.2;2.2 Genetic Algorithm;985
109.3.3;2.3 Rule-Based Heuristic;987
109.3.4;2.4 Simulation Model;989
109.3.5;2.5 Validation and Verification;989
109.4;3 Conclusion;991
109.5;Acknowledgment;991
109.6;References;992
110;Ranking of Private Turkish Universities: Proposal of New Indicators;993
110.1;Abstract;993
110.2;1 Introduction;993
110.3;2 Worldwide University Rankings;995
110.4;3 New Indicators Weights and the Methodology of UL Ranking;1000
110.4.1;3.1 Indicators and Weights of UL Ranking;1000
110.4.2;3.2 The methodology of UL Ranking;1001
110.5;4 Results and Analysis;1002
110.6;5 Conclusions;1003
110.7;Acknowledgment;1003
110.8;References;1003
111;Author Index;1006

Über Autor(innen)

Dr. Gunes Gencyilmaz is a professor in the Department of Industrial Engineering at Istanbul Aydin University. Previously he chaired the Department of Production Management (1980-2000) and was the director of Center for Production Research (1980-2000) at Istanbul University. He was the Head of Department of Management (2000-2010) and dean (2004-2009) at the Istanbul Kultur University. He is the graduate of Istanbul Technical University with a master’s degree in Mechanical Engineering (1959-1964), He completed a specialization program on operations research (1971-1973) at Federal Institute of Technology (ETH) Zürich. He holds a PhD degree on Production Management from Istanbul University (1973). As a researcher, he was at Cornell University (1996); Operational Research Department, British Gas Corporation (HQ), London, UK (1973-1975) and Technical University of Munich, Institute for Statistics and Applied Mathematics (1980-1981).

His current research interests include Industry 4.0, Modeling, Decision Analysis, Artificial Intelligence, Meta-Heuristics, and Production Systems

 He has organized numerous symposiums and conferences on production research, SMEs and productivity. He is the editor of 18 conference and symposium books. He served as an advisor in industry over the years. He managed several system projects of the Istanbul metropolitan municipality in the past.

He has been the advisor of numerous master’s and Ph.D thesis students. He is a member of several scientific societies. Currently, his Google Scholar Citation score is 1360. He holds scholarships and grants from Federal Institute of Technology Zürich (ETH), NATO System Sciences Division and the Alexander von Humboldt Foundation.

Prof. Dr. Numan M. Durakbasa is head of the research group “Industrial Metrology and Adaptronic Systems” of the Institute for Production Engineering and Photonic Technologies and head of the “Precision Metrology and Nanotechnology Laboratory” atTU Wien (Vienna University of Technology). He is Austrian expert in the International Technical Committee ISO/TC 213 "Geometrical Product Specifications and Verification", as well as ISO/TC 176 “Quality Management and Quality Assurance", vice chairman of the Austrian Standard Committee ON-K 031 “Geometrical Product Specifications and Verification, Technical Product Documentation“; expert in the Austrian Standard Committees “Quality Management Systems” and “Nano Technologies and Nano materials”. Professor Durakbasa is long-standing member of the Executive Committee of ÖGMA (Austrian Society for Measurement and Automatic Control), since 2016 GMAR (Society for Measurement, Automation and Robotics), Austrian delegate to the General Council of the International Measurement Confederation - IMEKO and expert in the TCs (TC 14, TC 7). He is also Founder member of Austrian “Forum Qualitäts-Wissenschaften – FQW (Forum Quality Sciences”. Professor Durakbasa has long-standing international practical experience as a “Quality Systems Auditor” and in the training and certification of quality professionals. He has experience in the development and implementation of management systems, in accreditation of inspection bodies and certification bodies for certification of management systems.

Research Interests

His major research areas are: interchangeable manufacturing, precision engineering, precision metrology, geometrical product specification and verification (GPS), industrial engineering, micro- and nanotechnology, co-ordinate metrology, Industry 4.0, telepresence, teleoperation, integrated management, quality management, environmental management, industrial metrology, measurement techniques, calibration, certification, assessment, inspection, and standardization.

 Publications

12 books and more than 500 scientific papers