Current Volume 9
In today's highly competitive manufacturing environment, reducing production cycle time has become a critical priority for organizations striving to improve efficiency, control costs, and remain globally competitive. For modern industrial organizations, extended cycle times restrict operational bandwidth and constrain capacity growth. In the automotive sector specifically, rapid technological evolution across electric vehicle (EV) ecosystems, autonomous driving platforms, connectivity suites, and sustainability-driven systems has amplified design complexities. Industry pioneers such as Tesla have forced manufacturers to dramatically compress development calendars to secure critical market capture. Despite significant advancements in computer-aided engineering, design-to-production cycles continue to experience severe bottlenecks. Unplanned equipment downtime represents a multi-billion-dollar operational risk, costing industrial firms an estimated USD 50 billion annually. Furthermore, the cross-functional coordination required between distributed research and development, procurement, and physical shop-floor assembly teams frequently introduces information decay, redundant engineering reviews, and extensive administrative wait times. Resolving these deep-seated coordination failures requires combining robust digital workflows with established process discipline frameworks.
IRE Journals:
Jay-ar Jose Vicente, Noel Florencondia, Mackenly A. Pernia "Optimizing Mechanical Design-to-Production Cycle Time: An Engineering Management Approach Using Lean Principles" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 3837-3844 https://doi.org/10.64388/IREV9I11-1718167
IEEE:
Jay-ar Jose Vicente, Noel Florencondia, Mackenly A. Pernia
"Optimizing Mechanical Design-to-Production Cycle Time: An Engineering Management Approach Using Lean Principles" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1718167