Webinar on 'Can you identify the causes of frequent rework due to minor dimensional deviations and distortions in each manufacturing process?'
A webinar will be held to address manufacturing challenges where minor dimensional deviations and distortions in each process accumulate, leading to frequent rework. The session will introduce solutions using 3D scanners to visualize these changes, identify root causes, and shift towards data-driven quality control.
📋 Article Processing Timeline
- 📰 Published: April 10, 2026 at 18:00
- 🔍 Collected: April 10, 2026 at 09:01
- 🤖 AI Analyzed: April 20, 2026 at 08:45 (239h 43m after Collected)
Cannot identify the cause of defects... The reality of the field where 'changes in each process are not visible'
In manufacturing sites, minor dimensional deviations and distortions occurring in each process accumulate and, in many cases, manifest as defects in the end.
However, because changes in each process are not recorded as data, it often leads to a situation where 'it's unknown which process caused the problem.'
As a result, it takes time to identify the cause, leading to increased costs due to rework and re-processing.
Why is it invisible? Personalized inspections make cause identification difficult.
Behind this state of 'unknown causes' lies an inspection system dependent on personal experience and intuition.
Since judgment criteria rely on individuals, fine changes in each process are not quantitatively accumulated, and as a result, the exact location where the defect occurred cannot be traced.
Furthermore, as technological succession does not progress, risks such as quality variations and oversights are increasing year by year.
'Visualization of changes in each process' realized with 3D scanners
This seminar will introduce methods to visualize changes in each process by utilizing 3D scanners to obtain high-precision data on the shape of manufactured products.
By measuring and recording at each process, we achieve rapid identification of defect locations and prevention of rework.
Furthermore, by accumulating measurement data, we support the transition to 'data-driven quality control,' looking ahead to quality standardization, traceability assurance, and future AI utilization.
Organizer/Co-organizer:
Amtek Corporation, Farro Clairform Division
Cooperation:
Open Source Software Research Institute Co., Ltd.
Majisemi Inc.
Majisemi will continue to hold webinars that are 'useful for participants.'
Past seminar materials and other currently open seminars can be viewed here.
In manufacturing sites, minor dimensional deviations and distortions occurring in each process accumulate and, in many cases, manifest as defects in the end.
However, because changes in each process are not recorded as data, it often leads to a situation where 'it's unknown which process caused the problem.'
As a result, it takes time to identify the cause, leading to increased costs due to rework and re-processing.
Why is it invisible? Personalized inspections make cause identification difficult.
Behind this state of 'unknown causes' lies an inspection system dependent on personal experience and intuition.
Since judgment criteria rely on individuals, fine changes in each process are not quantitatively accumulated, and as a result, the exact location where the defect occurred cannot be traced.
Furthermore, as technological succession does not progress, risks such as quality variations and oversights are increasing year by year.
'Visualization of changes in each process' realized with 3D scanners
This seminar will introduce methods to visualize changes in each process by utilizing 3D scanners to obtain high-precision data on the shape of manufactured products.
By measuring and recording at each process, we achieve rapid identification of defect locations and prevention of rework.
Furthermore, by accumulating measurement data, we support the transition to 'data-driven quality control,' looking ahead to quality standardization, traceability assurance, and future AI utilization.
Organizer/Co-organizer:
Amtek Corporation, Farro Clairform Division
Cooperation:
Open Source Software Research Institute Co., Ltd.
Majisemi Inc.
Majisemi will continue to hold webinars that are 'useful for participants.'
Past seminar materials and other currently open seminars can be viewed here.