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Smart Machining Processes
3. Faster responses to required changes
4. Increased flexibility toward introduction of new products
5. Improved accuracy and quality in manufacturing processes
6. Improved quality of products
7. Effective control of dataflows among various units
8. Reduction of lead times
9. Streamlined manufacturing flow from order to delivery
10. A holistic approach to enterprise-wide issues.
The so-called smart parts-based manufacturing systems ensure that each part is
correctly identified to perform reliable process control in such a flexible and customer-oriented manufacturing system. Uniquely identified individual parts can be
processed according to their specific requirements based on individual customer
preferences. Chen et al. (2020) describe how to use radio frequency identification
(RFID) in computer-integrated manufacturing as a lot identification system with the
following benefits:
• Low cost when compared with smart tag systems
• No need to detach tags while POD is cleaned
• Increased ease of carrier tracing
• Reduced probability of missing lots (when compared with smart tag
systems)
• Ease of maintaining the system and minimizing tag failure rate
• Reduced complexity of CIM system
• Operation benefit with smart tag
• Ability to fulfill a “place and go” scenario
• Is an easier to operate split function when compared with barcodes
3.2 SMART MANUFACTURING
Owing to recent advances in information technologies (IT) and operation technologies (OT), the manufacturing industry has entered the era of Industry 4.0 and the
traditional manufacturing technologies empowered by artificial intelligence and
the Industrial Internet of Things (IIoT) have become “smart” at handling the everincreasing complexity of tasks (Baroroh et al., 2020). Nowadays, it is imperative to
implement smart manufacturing that offers high production flexibility and efficiency
at acceptable costs; otherwise it is impossible to meet the rapidly growing consumer
demand for mass customized products (Baroroh et al., 2020).
Over the past years, the topic of smart manufacturing has been the focus of
researchers and manufacturing experts. Academic and industry researchers have
developed two paradigms to describe the deep integration of manufacturing and
advanced information technologies: smart manufacturing (SM) and intelligent manufacturing (IM) (Wang et al., 2021). The authors find that around 2000, IM was primarily associated with expert systems, fuzzy logic, neural networks, agent, flexible
manufacturing systems, CIM, and computer-aided design (CAD), while the early
phases of modern SM around 2010 are Industry 4.0 and automation. The most recent
Smart Machining Processes
3. Faster responses to required changes
4. Increased flexibility toward introduction of new products
5. Improved accuracy and quality in manufacturing processes
6. Improved quality of products
7. Effective control of dataflows among various units
8. Reduction of lead times
9. Streamlined manufacturing flow from order to delivery
10. A holistic approach to enterprise-wide issues.
The so-called smart parts-based manufacturing systems ensure that each part is
correctly identified to perform reliable process control in such a flexible and customer-oriented manufacturing system. Uniquely identified individual parts can be
processed according to their specific requirements based on individual customer
preferences. Chen et al. (2020) describe how to use radio frequency identification
(RFID) in computer-integrated manufacturing as a lot identification system with the
following benefits:
• Low cost when compared with smart tag systems
• No need to detach tags while POD is cleaned
• Increased ease of carrier tracing
• Reduced probability of missing lots (when compared with smart tag
systems)
• Ease of maintaining the system and minimizing tag failure rate
• Reduced complexity of CIM system
• Operation benefit with smart tag
• Ability to fulfill a “place and go” scenario
• Is an easier to operate split function when compared with barcodes
3.2 SMART MANUFACTURING
Owing to recent advances in information technologies (IT) and operation technologies (OT), the manufacturing industry has entered the era of Industry 4.0 and the
traditional manufacturing technologies empowered by artificial intelligence and
the Industrial Internet of Things (IIoT) have become “smart” at handling the everincreasing complexity of tasks (Baroroh et al., 2020). Nowadays, it is imperative to
implement smart manufacturing that offers high production flexibility and efficiency
at acceptable costs; otherwise it is impossible to meet the rapidly growing consumer
demand for mass customized products (Baroroh et al., 2020).
Over the past years, the topic of smart manufacturing has been the focus of
researchers and manufacturing experts. Academic and industry researchers have
developed two paradigms to describe the deep integration of manufacturing and
advanced information technologies: smart manufacturing (SM) and intelligent manufacturing (IM) (Wang et al., 2021). The authors find that around 2000, IM was primarily associated with expert systems, fuzzy logic, neural networks, agent, flexible
manufacturing systems, CIM, and computer-aided design (CAD), while the early
phases of modern SM around 2010 are Industry 4.0 and automation. The most recent