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By

Genesia Synclaire Tjoa 11601042

BACHELOR’S DEGREE in

MECHANICAL ENGINEERING – MECHATRONICS concentration ENGINEERING & INFORMATION TECHNOLOGY

SWISS GERMAN UNIVERSITY The Prominence Tower

Jalan Jalur Sutera Barat No. 15, Alam Sutera Tangerang, Banten 15143 – Indonesia

July 2020

Revision after Thesis Defense on 17th July 2020

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Genesia Synclaire Tjoa STATEMENT BY THE AUTHOR

I hereby declare that this submission is my own work and to the best of my knowledge, it contains no material previously published or written by another person, nor material which to a substantial extent has been accepted for the award of any other degree or diploma at any educational institution, except where due acknowledgement is made in the thesis.

Genesia Synclaire Tjoa

_____________________________________________

Student

______________

Date

Approved by:

Dr. Rusman Rusyadi

_____________________________________________

Thesis Advisor (SGU)

_______________

Date

Dipl.-Ing. Wolfgang Utsch

_____________________________________________

Thesis Co-Advisor (HF Mixing Group)

______________

Date

Dr. Maulahikmah Galinium, S.Kom., M.Sc.

_____________________________________________

Dean

______________

Date

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Genesia Synclaire Tjoa ABSTRACT

ONLINE CONDITION MONITORING WITH DATA VISUALIZATION AND PREDICTIVE ANALYSIS OF HF MIXERS’ HYDRAULIC PRESSURE UNIT

By

Genesia Synclaire Tjoa Dr. Rusman Rusyadi, Advisor Dipl.-Ing. Wolfgang Utsch, Co-Advisor

SWISS GERMAN UNIVERSITY

Due to optimizations demanded by Industry 4.0, an Online Condition Monitoring application is created for part of a rubber mixer line, namely the Hydraulic Pressure Unit, as a starting point. This is done by collecting the required data from the sensors and processing them on the PLC, sending the data to the PC using the ODK interface to be stored in a database, and visualizing the data into different charts for analysis in a PC user application. Rule-based data analysis is done to identify machine health status and simple Kalman Filter and Prediction is prototyped. By collecting and storing long- term PLC data, machine performance over time can be analyzed for predictive maintenance in the future.

Keywords: Online Condition Monitoring, Database, Data Visualization, Data Analysis, Predictive Analysis

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Genesia Synclaire Tjoa

© Copyright 2020 by Genesia Synclaire Tjoa

All rights reserved

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Genesia Synclaire Tjoa DEDICATION

I dedicate this work to HF Mixing Group and to its customers who will benefit from this application.

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Genesia Synclaire Tjoa ACKNOWLEDGEMENTS

From a complete change of thesis topic in the first week, to getting the German visa two days before my flight, to the pandemic that caused home office for two months and foiled my plans of going home, I thank my Lord Jesus for the strength through this rocky journey, for keeping me safe, and for the amazing people He put in my life.

To my parents, for getting me here with showers of love and support, and always believing I can achieve anything.

To Wolfgang and Simone, for being my German family, a roof over my head, spectacular food, and travels as much as the situation allowed; to Alica, for the many moves, miles, and talks in Herdorf’s surrounding forests.

To HF Mixing Group for having me again, for the chance to learn so much and be part of this big project, and for the future opportunities that are now possible for me in Germany. To Jens, for teaching me patiently everything PLC, and again Wolfgang, for teaching me patiently everything else.

To Pak Rusman, for the weekly dose of project enlightenment, and the constant reminder to actually write this thesis.

Last but not least, to Dion, Gaby, Acong, Leti, and Nita, my comrades through the past four years and this last strip of the battle, thanks for keeping in touch.

Know that all your support got me through this thesis, and beyond. Thank you for everything. You all are the best.

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Genesia Synclaire Tjoa TABLE OF CONTENTS

DEDICATION ... 5

ACKNOWLEDGEMEN TS ... 6

LIST OF FIGURES ... 10

LIST OF TABLES ... 13

LIST OF EQUATIONS ... 14

CHAPTER 1 - INTRODUCTION ... 15

1.1 Background ... 15

1.2. Research Problems ... 16

1.3. Research Objectives ... 16

1.4. Significance of Study ... 17

1.5. Research Questions ... 18

1.6. Hypothesis ... 18

CHAPTER 2 - LITERATURE REVIEW ... 19

2.1 Theoretical Perspectives... 19

2.1.1 Overview of O nline Condition Monitoring ... 19

2.1.2 Overview of Hydraulic Pressure Unit and Its Critical Parameters ... 20

2.1.3 The SIEMENS IPC Architecture ... 22

2.1.4 PLC-PC Communication and Function Calls ... 25

2.1.5 Using SQ Lite as Chosen Database Storage Interface ... 26

2.1.6 Using the ISA88 Standard and HFID ... 27

2.1.7 Using VB.NET WinForms in Visual Studio for User Application ... 29

2.1.8 Data Analysis Methods ... 30

2.1.9 Data Prediction Methods ... 30

2.2 Previous Studies ... 33

2.2.1 Optimizing Condition Monitoring of Big Data Systems ... 33

2.2.2 Condition Monitoring for Hydraulic Power Units - User-Oriented Entry in Industry 4.0 ... 34

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Genesia Synclaire Tjoa

Monitoring ... 35

2.2.4 A Visual Analytics Approach for Equipment Condition Monitoring in Smart Factories of Process Industry ... 35

2.2.5 Prediction and Scheduling of Maintenance by Condition Monitoring ... 36

2.2.6 Remaining Useful Life Prediction based on Noisy Condition Monitoring Signals using Constrained Kalman Filter ... 37

CHAPTER 3 – RESEARCH METHODS ... 38

3.1 Concept and Requirements... 38

3.1.1 Concept Development ... 38

3.1.2 Application Requirements ... 39

3.1.3 Software Sufficiency ... 40

3.2 Application Design... 41

3.2.1 Project Framework... 42

3.2.2 Components Description ... 43

3.2.3 Software Design... 45

3.3 Implementation... 66

3.4 Performance Tests ... 66

3.4.1 Subsystem Tests... 67

3.4.2 Integrated System Tests ... 71

3.5 Schedule Planning ... 73

CHAPTER 4 – RESULTS AND DISCUSSIONS... 75

4.1 Subsystem Test Results ... 75

4.1.1 Test Results of Subsystem 1: PLC Data Processing and Collection ... 75

4.1.2 Test Results of Subsystem 2: PLC Data Transfer and Database Storage .... 83

4.1.3 Test Results of Subsystem 3: Data Visualization ... 87

4.1.4 Test Results of Subsystem 4: Data Analysis and Prediction ... 100

4.2 Integrated System Test Results ... 106

4.2.1 Integrated PLC System Test Results ... 106

4.2.2 Integrated PC System Test Results ... 109

4.3 Software Sufficiency Evaluation... 111

CHAPTER 5 – CONCLUSIONS AND RECOMMENDATIONS ... 113

5.1 Conclusions ... 113

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Genesia Synclaire Tjoa

GLOSSARY ... 116

REFERENCES ... 117

APPENDICES ... 119

APPENDIX A-1. SUBSYSTEM 2 TEST RESULT ... 119

APPENDIX A-2. LOAD MENU SPEED TEST ... 119

APPENDIX A-3. PLC REALISTIC DATA TEST ... 120

APPENDIX A-4. PLC INTEGRATED SYSTEM LOAD TEST ... 120

APPENDIX A-4. PLC INTEGRATED SYSTEM RELIABILITY TEST... 121

CURRICULUM VITAE ... 122

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Genesia Synclaire Tjoa LIST OF FIGURES

Figure 1 - Condition Monitoring Equipment Market Regional Growth Rate (2020-

2025) (Mordor Intelligence, 2019)... 20

Figure 2 - Hydraulic Pressure Unit ... 20

Figure 3 – Front view of Siemens IPC 427E ... 23

Figure 4 - Connections of Siemens IPC 427E (Siemens, 2017) ... 23

Figure 5 - IPC 427E Architecture Visualization ... 24

Figure 6 - ISA88 Model Relationship... 28

Figure 7 - HFID components ... 29

Figure 8 - Mode State Flowchart in a HF HMI ... 29

Figure 9 - Kalman Filter Cycle ... 31

Figure 10 - In-situ Monitoring View and Radial Summary View ... 36

Figure 11 - Overall Program Flowchart ... 41

Figure 12 - Overall System Diagram ... 42

Figure 14 - ExtractMinMaxAverage Function Block Flowchart... 46

Figure 15 - HistogramRangeCounter Function Block Flowchart ... 48

Figure 16 - ODK OCM and Histogram PLC Data Types... 49

Figure 17 - OCM Type Data Export Flowchart ... 50

Figure 18 - Histogram Type Data Export Flowchart ... 51

Figure 19 - Copy OCM DB Button Implemented in Demo HMI ... 52

Figure 20 - UniqueID Database Tables... 53

Figure 21 - OCM Application Menu Design ... 53

Figure 22 - Snippet of UnitType (left) and EquipmentType (right) data tables ... 54

Figure 23 - Chart Menu Creation Flowchart... 55

Figure 24 - RangeStatus Table in UniqueID... 56

Figure 25 - ChartType Table in UniqueID ... 56

Figure 26 - SensorID2State Table in UniqueID ... 56

Figure 27 - Line Chart Design ... 57

Figure 28 - Closeup of Line Value Markers in Line Chart ... 57

Figure 29 - Create Line Chart Flowchart ... 58

Figure 30 - Bar Chart Stack View Design ... 59

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Genesia Synclaire Tjoa

Figure 32 - Create Bar Chart Flowchart... 60

Figure 33 - Spectrogram and Histogram Design ... 61

Figure 34 - Create Histogram Chart Flowchart ... 62

Figure 35 - Data Analysis Alerts Tab ... 63

Figure 36 - User Defined Prediction Parameters in User Application... 63

Figure 37 - Example of Reference Points and Prediction Line ... 65

Figure 38 - Data Analysis and Prediction Flowchart ... 65

Figure 39 - Simulated Sine Wave Data Block ... 75

Figure 40 - Trace using MainCycle time (left) and CyclicInterrupt time (right)... 76

Figure 41 - Trace Results of ExtractMinMaxAverage Test... 77

Figure 42 - Code Snippets of ExtractMinMaxAverage with Timer ... 78

Figure 43 - Code Snippets of ExtractMinMaxAverage with Time Compare ... 78

Figure 44 - Trace Results of ExtractMinMaxAverage Test... 79

Figure 45 - Snippet of Initial HistogramRangeCounter showing error return value ... 80

Figure 46 - HistogramRangeCounter’s Output Array for 5 Defined Range Borders .. 81

Figure 47 - HistogramRangeCounter’s Output Array for 10 Defined Borders ... 81

Figure 48 - Snippet of HistogramRangeCounter Function with 1019 Values ... 82

Figure 49 - HistogramRangeCounter’s Output Array for Range Counter ... 82

Figure 50 - Runtime Trace for HistogramRangeCounter Function ... 83

Figure 51 - Runtime Trace for Main FB ... 83

Figure 52 - Runtime Trace for Main OB ... 83

Figure 53 - ODK JustAddAndMultiply Trial Functions... 84

Figure 54 - HMI Screen for Sum Average ODK Trial ... 84

Figure 55 - Comparison of SQLite and PLC Data Entries ... 85

Figure 56 - (Clockwise from top left) PLC, ODK, SQLite, and VB Code Declarations of OCM Data... 87

Figure 57 - LoadMenu() Rows vs Runtime Test Results ... 90

Figure 58 - Create Line Chart Time vs Data Rows ... 91

Figure 59 - Create Bar Chart Time vs Data Rows ... 93

Figure 60 - Code Snippet and Resulting Spline of Polynomial Regression Curve ... 94

Figure 61 - Resulting Spectrogram and Spline of Polynomial Regression Curve ... 94

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Genesia Synclaire Tjoa

Figure 63 - Resulting Spectrogram and Gaussian Normal Curve Chart... 96

Figure 64 - Spectrogram with Full Custom Y Ticks... 97

Figure 65 - Spectrogram with Timestamp Annotation ... 97

Figure 66 - Create Spectrogram- Histogram Time vs Data Rows ... 99

Figure 67 - (Clockwise from top left) Blue-White, Black-White, HFBlue-White, Black-HFBlue-White Spectrogram Color Schemes ... 100

Figure 68 - (Clockwise from top left) Graph A, B, C, E, D for Kalman Trial 1 ... 102

Figure 69 - (Clockwise from top left) Graph A, B, C for Kalman Trial 2 ... 104

Figure 70 - Code Snippet and Trace of Simulated Data with Noise ... 106

Figure 71 - Code Snippet Showing Bypassed States for PLC Testing ... 107

Figure 72 - Snippet of Water Saturation Measurement’s Trigger Counter ... 107

Figure 73 - PC System Data in Data Export Test ... 108

Figure 74 - Data Counts in Data Export Test ... 108

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Genesia Synclaire Tjoa LIST OF TABLES

Table 1 - Required HPU sensor data for OCM ... 21

Table 2 - Software Sufficiency Table ... 40

Table 3 - PLC Test Measurement Parameters ... 73

Table 4 - Project Schedule Planning ... 74

Table 5 - PLC Write to Local Buffer Test Results ... 85

Table 6 - PLC and SQLite Data Comparison 1 ... 86

Table 7 - Equivalent Data Types based on the Siemens ODK Manual ... 86

Table 8 - Test Results of Subsystem 3: Data Visualization ... 88

Table 9 - SQLite Select Rows Test Results ... 89

Table 10 - SQLite Select Columns and Rows Test Results ... 89

Table 11 - Speed Test Results of Line Chart Creation ... 91

Table 12 - Speed Test Results of Bar Chart Creation ... 92

Table 13 - Speed Test Results of CreateSpectrogram() Function... 98

Table 14 - Speed Test Results of Spectrogram- Histogram Creation ... 99

Table 15 - Data Analysis Test Results ... 101

Table 16 - Process and Measurement Noise for Kalman Trial 1 ... 101

Table 17 - Process and Measurement Noise Table for Kalman Trial 1 ... 103

Table 18 - Kalman Prediction Function Speed Test Results ... 105

Table 19 - Test Results of Integrated PC System ... 110

Table 20 - Software Sufficiency Results ... 111

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Genesia Synclaire Tjoa LIST OF EQUATIONS

Equation 1 - State Vector Matrix X ... 32

Equation 2 - Process Covariance Matrix P ... 32

Equation 3 - State Transition Matrix F ... 32

Equation 4 - Next State Vector Matrix ... 32

Equation 5 - Measurement Matrix H ... 64

Equation 6 - Transition Matrix F ... 64

Equation 7 - Gaussian Normal ... 95

Equation 8 - Standard Deviation ... 95

Referensi

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