• Changing corporate culture and climate and continuous learning In the process of implementing DX, there is often a need to innovate the corporate culture and climate and continuously learn new technologies and methods. [...] This ability is: “To understand the corporate philosophy, the environment surrounding the company, and the company itself, by organically combining digital technology and kaizen, to build a company-wide or factory-wide digitalization roadmap, and to support and execute projects to realize the roadmap.” (Figure 2) FIGURE 1-2 ABILITY TO CONCEPTuALIZE dIGITALIZATION In other words, digitalization con. [...] It is necessary to know in advance how much degradation is acceptable and how long the sensor’s life will be and to estimate the timing of replacement in advance. [...] Because of the strict and complex logical structure of RDBs, the larger the data, the slower the processing speed. [...] The larger the system, the more the limitations of these tools will surface and may spiral out of control.
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Table of Contents
- FOREWORD 9
- SECTION 1 Introduction 11
- Chapter 1.1 Foreword 11
- Chapter 1.2 Structure of this Guidebook 12
- Chapter 1.3 Digital Kaizen 12
- 1.3.1 What is Digital Kaizen? 12
- 1.3.2 DX and Kaizen 13
- 1.3.3 Digital Innovation Trends in the construction of the “Figure 3-1 Target System,” the goal is to gaine Manufacturing Industry 14
- Chapter 1.4 Ability to Conceptualize Digitalization 16
- 1.4.1 What is the Ability to Conceptualize Digitalization? 16
- 1.4.2 Knowledge of Digitalization 16
- 1.4.3 The Philosophy of Kaizen 17
- Chapter 1.5 Reskilling 18
- SECTION 2 IoT Basics 20
- Chapter 2.1 What is IoT? 20
- Chapter 2.2 Bridging the Real World and Cyberspace 21
- Chapter 2.3 Various Sensors Used in Factories 22
- Chapter 2.4 Microcontrollers Used in IoT 24
- Chapter 2.5 IoT Wireless Area Network 25
- Chapter 2.6 LPWA (Low-Power Wide-Area) 26
- Chapter 2.7 Cloud Computing and IoT Platforms 27
- Chapter 2.8 AWS, Azure, Google Cloud Platform 29
- Chapter 2.9 How to Store Data 31
- Chapter 2.10 Data Visualization 33
- Chapter 2.11 Sending Alerts 35
- Chapter 2.12 Programming 36
- 2.12.1 Programming of IoT devices 36
- 2.12.2 Language Characteristics 37
- 2.12.3 Integrated Development Environment (IDE) 37
- 2.12.4 Using GitHub 39
- 2.12.5 No Code/Low Code 40
- Chapter 2.13 AI in Manufacturing 42
- Chapter 2.14 Machine Vision 43
- 2.14.1 Traditional Machine Vision and the Rise of AI 44
- 2.14.2 Machine Vision Image Preprocessing 44
- 2.14.3 Neural Network 48
- 2.14.4 Convolution Neural Network 50
- 2.14.5 YOLO 52
- SECTION 3 Digital Kaizen Case Studies 54
- Chapter 3.1 Legacy Equipment Retrofit Case Study: Production Control and Abnormality Detection in an Auto Parts Company 54
- 3.1.1 Importance of Retrofit in Kaizen 54
- 3.1.2 Current Status and Issues of Company A’s Automotive Parts Plant 55
- 3.1.3 Digital Kaizen Initiatives and Effectiveness 57
- 3.1.4 Future Prospects: Next Kaizen 63
- 3.1.5 Digital Technologies Used 63
- Chapter 3.2 Production Management Kaizen Case Study: Visualization and Utilization of Production Data in a Confectionery Factory 65
- 3.2.1 Importance of production control in Kaizen 65
- 3.2.2 Company B's Confectionery Factory: Current Status and Issues 66
- 3.2.3 Digital Kaizen Initiatives and Effectiveness 69
- 3.2.4 Future Prospects: Next Kaizen 73
- 3.2.5 Digital Technologies Used 73
- Chapter 3.3 Environmental Improvement Case Study: Visualization of Environmental Parameters at a Cosmetics Company 74
- 3.3.1 Importance of Measuring Environmental Parameters in Kaizen 74
- 3.3.2 Company C’s Cosmetics Factory: Current Status and Issues 75
- 3.3.3 Digital Kaizen Initiatives and Effectiveness 77
- 3.3.4 Future Prospects: Next Kaizen 84
- 3.3.5 Digital Technologies Used 84
- Chapter 3.4 Inventory Management Case Study: Introducing an RFID System in a Hand Tools Company 86
- 3.4.1 Importance of Inventory Management in Kaizen 86
- 3.4.2 Current Status and Issues of Company D’s Production Process 87
- 3.4.3 Digital Kaizen Initiatives and Effectiveness 90
- 3.4.4 Digital Technologies Used 95
- Chapter 3.5 Equipment Monitoring Case Study: Quality Improvement by Introducing an Equipment Monitoring System to an Ultrasonic Gel Manufacturing Company 96
- 3.5.1 Importance of Equipment Monitoring in Kaizen 96
- 3.5.2 Company E’s Current Status and Issues 97
- 3.5.3 Digital Kaizen Initiatives and Effectiveness 99
- 3.5.4 Digital Technologies Used 102
- Chapter 3.6 System Integration Case Study: Integrating Various Data and Equipment at a Metal Stamping Company 102
- 2.6.1 Importance of Information System Integration in Kaizen 102
- 3.6.2 Current Status and Issues of Company F’s Production Process 103
- 3.6.3 Digital Kaizen Initiatives and Effectiveness 105
- 3.6.4 Digital Technologies Used 112
- SECTION 4 Learn the Technology for Digital Kaizen 113
- Chapter 4.1 Building the Raspberry Pi Development Environment 114
- 4.1.1 What is the Raspberry Pi? 114
- 4.1.2 Raspberry Pi Family 115
- 4.1.3 Raspberry Pi board configuration 116
- 4.1.4 Raspberry Pi Software Development 117
- 4.1.5 Initial Settings of the Raspberry Pi 119
- 4.1.6 VNC setup and activation 122
- 4.1.7 Using Visual Studio Code 127
- 4.1.8 Python Programming for Beginners 134
- Chapter 4.2 Visualization of Equipment Operating Conditions Using Sensors 138
- 4.2.1 Importance of Visualization of Operating Conditions in Kaizen 138
- 4.2.2 Types of Sensors Used for Object Detection 138
- 4.2.3 Creating a Parts Counting System 139
- 4.2.4 Proximity Sensor MDS-F4-5V [74] 140
- 4.2.5 Connecting the MDS-F4-5V to the Raspberry Pi 141
- 4.2.6 Python Programming of the Parts Counting System 142
- Chapter 4.3 Acquisition of Environmental Sensor Data 144
- 4.3.1 Importance of Environmental Data Acquisition in Kaizen 144
- 4.3.2 Available Environmental Sensors 145
- 4.3.3 Configuration of Environmental Parameter Acquisition System 145
- 4.3.4 Understanding the Environmental Sensor BME280 146
- 4.3.5 Connecting the BME280 to the Raspberry Pi 147
- 4.3.6 Overview of I2C Interface 148
- 4.3.7 Preparing for Cloud Service and Programming 148
- 4.3.8 Phyton Program to Process Environmental Parameters 151
- 4.3.9 Start the Program Periodically 153
- 4.3.10 Observation of Environmental Parameters by the Cloud Service 154
- Chapter 4.4 Saving Environmental Sensor Data to a File 155
- 4.4.1 Export to CSV file on Raspberry Pi 155
- Chapter 4.5 Real-Time Synchronization of Data 160
- 4.5.1 Export to InfluxDB Cloud 161
- Chapter 4.6 Data Visualization and Alert Transmission 172
- 4.6.1 Visualization and Alerting with InfluxDB Cloud and Grafana Cloud 173
- Chapter 4.7 Anomaly Detection Using Sensors 190
- 4.7.1 Importance of Anomaly Detection in Kaizen 190
- 4.7.2 Creating a Motor Anomaly Detection System 190
- 4.7.3 Driving a DC Motor by PWM 191
- 4.7.4 Connecting the motor, current sensor INA219, and the Raspberry Pi 192
- 4.7.5 Anomaly Detection Strategy 193
- 4.7.6 Python Programming of the Anomalies Detection System 197
- SECTION 5 How to Proceed with a Project 200
- Chapter 5.1 How to Proceed with a Project Suitable for Digital Kaizen 200
- Chapter 5.2 How to Proceed with Agile Project Management 203
- 5.2.1 Origins of Scrum 203
- 5.2.2 Characteristics of Scrum 203
- 5.2.3 Overview of the Scrum Framework 204
- 5.2.4 Project Promotion Structure in Scrum and an Image of How It Is Applied to Digital Kaizen 206
- 5.2.5 How to Proceed with a Project in Scrum and an Image of How it is Applied to Digital Kaizen 210
- Chapter 5.3 Deliverables at Project Completion 218
- 5.3.1 Purpose of Systemization 218
- 5.3.2 System Configuration Diagram 219
- 5.3.3 List of Devices Used 219
- Chapter 5.4 How to proceed when using an IT vendor 221
- 5.4.1 How to Select a Vendor 221
- 5.4.2 Important Points on How to Conclude a Contract 222
- References 223
- Section 1-4 223
- Section 5 227
