After analysing 35 million machine hours across 200 machines in indian shop floors , Here is what we found
Before Industry 4.0 Implementation
| Metric | Lowest | Highest |
|---|---|---|
| OEE (Overall Equipment Effectiveness) | 35% | 50% |
| Spindle Utilization (CNC Machines) | 14% | 35% |
| Operator Work Ethics (Downtime) | 5% | 30% |
| Effect of Late Start / Early Stoppage | 10 min/shift (2%) | 60 min/shift (14%) |
| Night Shift Downtime | 3 min/shift | 4 hrs/shift |
| Parts Count Difference (Reported vs Actual) | 1% | 5% |
| Cycle Time Deviation (Actual vs Standard) | 0% | 20% |
After Industry 4.0 Implementation
| Metric | Lowest | Highest |
|---|---|---|
| Increase in OEE | +18% | +33% |
| ROI (Revenue Benefit) | 3x in 10 days | 60x in 60 days |
Why is Data important ?
There are big doubts about what industry 4.0 does, and what its benefits are .
India is no longer a low-cost country; it is a low-productivity country. This study shows the effect of data from an Industry 4.0 machine monitoring system across various shop floors.
Where is this Data from ?
Big Data collected from 2,000 machines on high-mix, low-volume (HMLV) shop floors across India, covering a wide range of metal-cutting and metal-forming industries in discrete manufacturing.
Ranging from MSMEs with 20 machines to large corporations with 1,200 machines, a total of 35 million machine hours has been collected by a Machine Monitoring System.
BEFORE implementation of industry 4.0 for machine data collection for LEAN
OEE of shop floor
OEE (Overall Equipment Effectiveness), weighted for the whole shop .
Highest - 50%
Lowest - 35 %
Spindle Utilization in CNC machines
Spindle running time as % of planned production time in aerospace firms .
Highest - 35%
Lowest - 14%
Operator work ethics
Machine Downtime due to poor operator work ethics in an 8 hour shift .
Highest - 30%
Lowest - 5%
Effect of late start , early stoppage
Downtime due to machines starting late at shift start and stopping early at shift end as % of planned production time during an 8 hour shift .
10min/shift - 2%
60min/shift - 14%
Downtime in night shift
Machine downtime due to extended period of zero production as % of planned production time during an 8-hour night shift .
Lowest : 3 min / shift
Highest : 4 hrs / shift
Parts count difference Reported vs Actual
Parts count difference between produced quantity reported by the operator vs Actual production quantity .
Lowest - 1%
Highest - 5%
Cycle time deviation Actual vs Standard
Cycle time difference between actual cycle time and standard cycle time as % .
Lowest - 0%
Highest - 20%
AFTER implementation of industry 4.0 for machine data collection by LEAN
Capacity utilization Effect of industry 4.0
Increase in OEE after implementation of machine monitoring system.
Lowest - 18%
Highest - 33%
Return on Investment (ROI)
Revenue benefit of machine monitoring system compared to the cost of the system
60x in 60 days
3x in 10 days
Conclusion
With traditional manual , paper based data collection , machine capacity utilization is 50% or less in HMLV (high mix low volume ) shop floors .
ROI is like paying for a full banana , but eating only 50% or less .
Key Takeaway :
Data is king , More machines CANNOT improve profitability but accurate data can.
