**Global automotive manufacturing sector**: A leading interiors manufacturer has deployed ThroughPut Inc’s AI-powered supply chain platform across 110 facilities, enhancing Just-in-Time operations, reducing defects by 30%, cutting downtime, and delivering $20 million in annual savings without new infrastructure investment.
A leading Automotive Interiors Manufacturer with a global footprint has successfully implemented an AI-powered supply chain optimisation platform developed by ThroughPut Inc, enabling the company to advance its Just-in-Time (JIT) manufacturing capabilities across all operational shifts. The deployment took place across the manufacturer’s extensive network, which spans over 110 facilities worldwide that produce advanced automotive interior systems for major car manufacturers.
Before adopting the solution, the company faced several challenges typical of modern manufacturing environments, including inefficiencies and unexpected downtime despite operating continuously. Quality inconsistencies led to frequent recalls, directly impacting costs. The manufacturer also lacked real-time data necessary for efficient capacity planning, which resulted in poor shift balancing, suboptimal resource allocation, and unstable production throughput. Traditional tools were inadequate for identifying processes that were degrading performance. Additionally, manual reporting and decision-making methods delayed improvement efforts.
To address these challenges, the company implemented ThroughPut’s Supply Chain Decision Intelligence & Analytics Platform. This AI-driven solution deploys over 42 advanced algorithms to analyse time-series data from production lines. It classifies processes as stable or unstable using econometrics and signal processing techniques and offers actionable recommendations to reduce fluctuations in inventory movement, production flow, and shift output.
A key feature of the platform enables “what-if” simulation scenarios for capacity planning. These simulations assist planners in optimising labour distribution across shifts, improving fulfillment plans, and managing cart movements and availability in real time. This capability has led to a more responsive JIT delivery system and decreased idle time.
Analysing shift-level performance revealed that one shift, specifically Shift 3, was producing three times as many defects as the other shifts combined. Using insights from the platform, the company rebalanced cart distribution and operator workload to improve quality and reduce defects by up to 30% in underperforming shifts.
The implementation also embraced Lean Six Sigma methodologies, focusing on labour optimisation, logistics improvement, and intelligent inventory flow management. By integrating cross-functional data from production, quality, inventory, and logistics, the platform created a unified data environment, replacing manual checks with real-time dashboards and facilitating data-driven operational decisions.
The outcomes were significant. The company achieved over $20 million in projected annual supply chain savings, improved labour productivity and cart utilisation, and reduced unexpected downtime, contributing an estimated $2 million increase in cash flow. The speed of decision-making increased fivefold due to real-time data analysis, enabling faster responses to emerging issues. Additionally, the manufacturer realised an annual value gain in output ranging from $0.5 million to $3 million.
Importantly, these improvements were realised without the need for new infrastructure investments, demonstrating the platform’s compatibility with existing Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MES), Warehouse Management Systems (WMS), and production systems.
ThroughPut’s platform offers additional benefits, delivering rapid return on investment within 90 days and customised insights tailored to specific industries, including automotive, electronics, and fast-moving consumer goods (FMCG). Its patented AI algorithms, grounded in econometrics, signal processing, and machine learning, provide higher prediction accuracy compared to conventional supply chain analytics tools.
Reflecting on the project’s impact, the implementation shows how advanced AI-powered supply chain solutions can support automotive manufacturers in transitioning from reactive, manual operations to intelligent, automated workflows that enhance Just-in-Time manufacturing. The results include minimised unplanned downtime, stabilised quality across shifts, improved resource allocation, and significant cost savings.
The automation and insights provided by the platform enable manufacturers to anticipate bottlenecks, optimise labour distribution for better shift-wise performance, and use real-time operational intelligence to drive bottom-line improvements. This case illustrates the growing role of artificial intelligence in addressing the complexities of modern manufacturing supply chains.
Source: Noah Wire Services
