Case Study: Hope’s Windows, Inc. – Increasing Efficiency within Final Assembly Process

Hope’s Windows is the preeminent designer and manufacturer of steel windows and doors in the US. Hope’s Windows is a 100+ year old company focused on producing premium-quality custom windows and doors for residential and commercial new construction, retro fit, and historic preservation.

Insyte helped us see where the bottlenecks were in our current system and provided us with solutions to improve our flow of orders.

– Rob DuBois, Vice President of Operations

SITUATION

Hope’s Windows has multiple plants on their campus. Plant 1 houses the fabrication processes, which are then sent to Plant 3 for finishing operations (i.e. inspection, outside coating, prime, paint, final assembly, and packaging). An increase in sales volume led to some production issues that contributed to a negative effect on Hope’s Windows’ throughput and on-time delivery. The lead time increased from approximately 15 weeks to over 19 weeks.

SOLUTION

Hope’s Windows engaged Insyte Consulting to access the current state of the operations in Plant 3. A current state value stream map of the operations was created to help pinpoint the areas that were bottlenecks in moving material through the system.

Based on the assessment, Insyte provided the company with a series of recommendations. The recommendations included utilizing the concept of division of labor within the assembly cells, establishing and posting production expectations for each job, organizing work areas with visual cues, establishing a designated area for required components, and ensuring upstream processes were correct prior to reaching the assembly cells.

The Hope’s Window’ project team prioritized these recommendations and an action plan for implementation was created and executed to guide the workforce in implementing the improvements that will decrease lead time, increase on-time delivery, and increase throughput.

RESULTS

  • Estimated 4-week reduction in lead time (20% decrease).
  • Anticipated 30% increase in throughput as measured in hours / piece.
  • Significant improvement in on-time delivery from 30% to >70%.
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