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CASE STUDY- Construction Equipment Manufacturer Improves Line Efficiency
VIMANA’s IoT Solutions for Smart Manufacturing:
Line Performance Management, Lean Processes.
Company Background
This construction equipment manufacturer provides innovative solutions for underground construction and trenching. They have eight manufacturing facilities and a robust dealer network selling in over 100 countries. The company prides itself on leadership in innovation, customer service, and a strong culture for continuous improvement.
Challenge
In an ongoing effort to optimize manufacturing processes, the continuous improvement team identified the paint line as a potential bottleneck in the production process. There was excess build-up of work-in-process inventory in front of the paint line and a 5-7 month delay in part production. The team needed a data-driven approach to evaluate line performance, identify and eliminate waste.
Solution
Construction Equipment Manufacturer uses Analytics for Real-time Insight into Bottlenecks
At first, the continuous improvement team used a stopwatch and manual data collection to evaluate the paint lines’ efficiency. This process was error-prone and resource-intensive. Then, with VIMANA’s IoT Connectivity, IoT data was collected automatically from the conveyer monorail system in real-time from each point along the paint line by wiring the stop buttons to a Moxa I/O hardware data collector.
First, VIMANA’s industrial analytics provided insight into paint line’s performance, bottlenecks, and unplanned downtime. Second, the team identified the primary bottleneck areas to be the Topcoat Booth, Blow Off Booth, Load and Unload Station, Cure Oven, and Dry Off Oven. However, more in-depth knowledge was needed to find waste and lean processes. Third, VIMANA’s Operator Panel was customized to expand downtime classifications. As a result, the increased categorization provided more detailed insight into the causes, duration, and frequency of downtime. With this information they uncovered that machine and tooling failure, part inspection delays, and waiting for materials were significant causes of production line delays. Therefore, these value stream steps were a high priority for lean process improvement.
Over time, VIMANA’s historical reports provided the information to establish a 70%-line efficiency target. Actual line performance compared to this target is monitored and evaluated in real-time to ensure line productivity.
In addition, VIMANA’s analytics informed day-to-day decisions to help them optimize the process flow and cycle time. When stoppages exceed 30-minute thresholds, predictive alerts notified employees so that operators could quickly address line issues proactively.
Business Outcomes
VIMANA’s Industrial Analytics provided the operational intelligence to drive lean paint line processes, which reduced delays, WIP inventory, and production costs. Performance targets and documented methods provided a new standard for work and best practice sharing across shifts.
- Overall line utilization went from 30% to 72% utilization in 6 months and the standard of work increased throughput and process stability.
- Overall unplanned downtime declined from 11% to 4% in 5 months.
- One paint line reduced labor costs by $250,000 in 6 months. They realized 13 hours/week savings in indirect labor hours, producing the same output with fewer resources.
- VIMANA’s data-driven insight cost justified the purchase of an incremental paint line removing the constraint to meet demand.
