Partner with Axonsemi to transform your supply chain, procurement, and industrial operations through our proven BPE and Decision Support methodologies.
Contact Us TodayWe help semiconductor companies optimize supply chain, procurement, and industrial operations by combining deep industry experience with business process engineering and advanced decision support capabilities.
Our consultants have 60+ years of combined experience from top tier semiconductor companies in operations, procurement, logistics, industrial and process engineering.
The semiconductor industry is undergoing massive transformation; we bring unique value by combining deep operational knowledge with modern digital practices.
Process Identification → Documentation → Improvement Opportunities → Training → Maintenance → Success Metrics and Reporting → Audit Support
Need Identification → Decision Support Tool Prototyping → Documentation and Training → Maintenance and Audit Support
| Challenge | Our Solution |
|---|---|
| Long lead times | Streamline material and supplier flows |
| Spare parts shortages | Adjust stocking levels using predictive analytics |
| Siloed data, no visibility | DS dashboards and real-time KPIs |
| Excess inventory | Inventory optimization and sourcing redesign |
| Inefficient fab layout | Lean redesign and capacity modeling |
| Capacity planning | Decision support through capacity modeling |
A high-impact, fast-track diagnostic engagement designed to quickly identify bottlenecks and improvement opportunities in top underperforming logistics, procurement, or industrial engineering processes.
Execute the prioritized process improvements to transform semiconductor operations, delivering measurable business impact. Diagnose additional processes and execute improvements.
Our consulting engagements are designed to assess and analyze existing or envisioned processes to identify inefficiencies, bottlenecks, and opportunities for improvement.
| Offering | Timeline | Objective | Outcome |
|---|---|---|---|
| Rapid Diagnostic | 6 Weeks | Quickly identify & prioritize process improvement opportunities | Clear roadmap with ROI case |
| Comprehensive Support | Project-Based / Month-to-Month | Redesign & embed new logistics processes | Measurable operational improvements |
Assess existing critical materials management processes and tools. Identify opportunities to use predictive analytics to optimize inventory levels by setting forward-looking stocking levels and aligning lead-time-based purchase order deliveries with production needs. Adjust existing or develop new tools to provide improved tactical decision support to proactively manage deliveries and lead-times from existing suppliers or begin sourcing from alternative suppliers if necessary.
Who is it for?
Fabs and ATs with critical materials inventory
Fabs and ATs looking to better manage their critical materials
What you get:
Duration:
6–8 Weeks Pilot Project, 4–6+ Months Comprehensive Support
Impact:
Provided buyer/planners at a mature wafer fab with improved process and tactical decision support tools to better manage critical indirect materials. Chemical, gas, and target lead-times and inventory control improved significantly. Regular updates and reviews of the tactical decision support tools highlighted future inventory shortfalls as well as overages, giving buyers sufficient time to proactively manage purchase order delivery dates and lead-times to optimize inventory levels on an ongoing basis.
Assess existing processes and tools used to manage warehouse capacity for storage of spare parts, direct, and critical indirect materials. Identify opportunities to use predictive analytics and supplier relationships to align internal and external warehouse capacity with production needs.
Who is it for?
Fabs and ATs with spare parts, direct, and critical indirect inventory
Fabs and ATs looking to improve warehouse capacity management
What you get:
Duration:
6–8 Weeks Pilot Project, 4–6+ Months Comprehensive Support
Impact:
Worked with the direct materials procurement team of a major semiconductor company to properly understand wafer storage space requirements and predict future capacity needs for a warehouse supporting multiple wafer fabs ramping simultaneously. Provided inputs to the capital justification process for the required warehouse expansion to be completed in time to support production ramps.
Map existing supply chain management process(es) to comprehend complex interactions between all internal and external participants. Identify process gaps and provide improvement recommendations. Determine KPIs and identify reporting needs to successfully monitor processes moving forward.
Who is it for?
Fabs and ATs looking to improve existing supply chain processes
What you get:
Duration:
6–8 Weeks Pilot Project, 4–6+ Months Comprehensive Support
Impact:
Mapped and reviewed existing spare parts repair process at a mature wafer fab where repairs were a consistent problem—either because expensive new parts had to be bought instead of repaired ones, raising costs, or because new parts were obsolete.
Identified and closed process gaps caused by lack of monitoring and coordination. Established KPIs and reporting to monitor repairs consistently.
Repair service levels improved from 70–80% to above 90%, often reaching 100%, and morale increased as the process became more effective.
Assess existing spare parts inventory management processes and tools. Identify opportunities to use predictive analytics to optimize inventory levels by setting forward-looking stocking levels based on historical spare parts usage at known production levels. Establish regular review process to ensure stocking levels are aligned with demand-driven forecasts.
Who is it for?
Fabs and ATs with spare parts inventory
Fabs and ATs looking to align spare parts inventory with production
What you get:
Duration:
6–8 Weeks Pilot Project, 4–6+ Months Comprehensive Support
Impact:
Determined future stocking levels for a combined spare parts warehouse for multiple fabs using predictive analytics based on historical usage and production levels.
Calculated ramp-appropriate stocking levels, allowing all fabs to ramp simultaneously with minimal operational impact.
Assess existing procurement processes and tools. Identify process gaps and opportunities to improve supplier reliability, lead times, and quality, achieve cost reductions, lower supply chain risks, and improve regulatory compliance.
Who is it for?
Fabs and ATs with internal procurement operations
Fabs and ATs looking to improve procurement processes
What you get:
Duration:
6–8 Weeks Pilot Project, 4–6+ Months Comprehensive Support
Impact:
During worldwide quartz and silicon carbide supply shortages, tightened supplier relationships and improved supply chain controls with multiple suppliers to fully understand lead-time changes, ensure ongoing supply of critical parts, and lower costs by avoiding expedite fees.
Audited a chemical distributor warehouse to lower warehouse safety risks from weather events. Established intermediate stocking agreements with distributors to provide back-up stock availability within a one-day delivery window, reducing risk of delays.
Assess existing capacity modeling capability and create a static capacity model based on customer equipment sets, process flows, and expected incoming material volumes to identify needed equipment, process, and operational changes.
Who is it for?
Fabs and ATs with limited or no capacity modeling capabilities
Fabs and ATs looking to better manage capacity and operations
What you get:
Duration:
6–8 Weeks Pilot Project, 4–6+ Months Comprehensive Support
Impact:
A static fab capacity model was created and used to determine capabilities for handling wafer loadings, justify capital projects, evaluate process changes, and maintain model input accuracy for continuous improvement.
At an OSAT site, a capacity model identified equipment needs, reduced uncontrolled WIP build-up, and improved understanding of throughput and process flow accuracy.
Example client profile – A leading semiconductor manufacturer specializing in advanced node technologies, experiencing challenges in maintaining consistent yield rates and optimizing production efficiency.
Phase 1 – Diagnostic Assessment
Phase 2 – Strategy Development
Phase 3 – Implementation and Training
Phase 4 – Monitoring and Continuous Improvement
Yield Improvement:
The client achieved a 20% increase in yield rates within six months, significantly reducing scrap and rework costs.
Figure 1 — Yield Rates Improvement (Month 1–12)
Defect Rate Reduction:
The client saw a notable reduction in defect rates, particularly in critical process steps, enhancing overall product quality and reliability.
Figure 2 — Defect Rates Reduction (Before/After)
Process Efficiency:
The implementation of lean manufacturing practices resulted in a 15% reduction in cycle times, accelerating the client's time-to-market for new products.
Figure 3 — Cycle Times Reduction (Month 1–12)
Tool Uptime:
Improved tool maintenance and standardized qualification protocols led to a 12% increase in tool uptime, enhancing overall production capacity.
Figure 4 — Tool Uptime Improvement (Month 1–12)
Cumulative Cost Savings:
Continuous cost savings are realized as a result of improved yield, shorter cycle times, and increased tool uptime.
Figure 5 — Cumulative Cost Savings Over Time
The client expressed high satisfaction with the engagement, particularly appreciating the tailored solutions and proactive support throughout the project. Clear communication and effective training were highlighted as key factors in the successful adoption of the new practices.
This case study demonstrates Axonsemi's ability to significantly enhance yield stability and process efficiency in semiconductor manufacturing. By aligning strategies with the client's specific goals, measurable improvements were achieved in yield, throughput, and tool reliability, fostering a strong partnership for future growth.
Partner with Axonsemi to transform your supply chain, procurement, and industrial operations through our proven BPE and Decision Support methodologies.
Contact Us Today