About Three Sigma Technologies

Implementation Goals

Three Sigma aimed to address critical challenges in its production process by implementing Skody AI (Advanced Planning Scheduling), with the following objectives:

• Reduce production delays by optimizing scheduling
• Adapt schedules dynamically to account for machine availability, employee downtime and material delays
• Streamline production planning processes for greater efficiency
• Replace Excel-based scheduling with a more advanced, automated easy to use tool

The Challenge: Inefficient Excel-Based Scheduling

Three Sigma’s complex production processes required sophisticated scheduling solutions. Initially, the company relied on Excel, which, while functional as a spreadsheet, fell short for advanced production planning. The lack of a standardized scheduling approach led to inconsistent project quotes and deliverables. Newer team members struggled to produce reliable estimates, relying heavily on the intuition of senior staff. This dependence on tribal knowledge created bottlenecks, single points of failure, and inefficiencies in the scheduling workflow.

Why Scheduling Wasn’t the Sole Objective

While replacing Excel was necessary, the primary goal of adopting Skody AI APS was to meet the aerospace industry’s demanding requirements and customer expectations. Beyond reducing inventory, Three Sigma needed to align production schedules with material availability. Working with suppliers serving aerospace industry giants, the company faced frequent component delays, which disrupted production. Previously, creating a production schedule took four days, and any delay in material delivery or machine availability required restarting the process, causing further delays and underutilized machine capacity. Adopting Skody AI APS became essential to streamline operations and enhance flexibility.

Phased Implementation for Maximum Impact

To maximize efficiency, Three Sigma implemented Skody AI APS in a single production section—focusing on CNC machining, where component availability issues had the greatest impact on costs. While scheduling the entire production process (CNC machining, precision component manufacturing, and final assembly) was an option, a phased approach ensured quicker results. The initial outcomes were transformative: the scheduling process, once taking three to four days, was reduced to just two hours. Schedules are now generated in seconds, allowing employees to analyze resource availability and utilization within the two-hour window, significantly boosting operational efficiency.

Measurable Results of Skody AI APS

The implementation of Skody AI APS delivered substantial benefits:

• Reduced Scheduling Time and Inventory: Scheduling time dropped from days to hours, and inventory levels decreased by 15%.
• ERP Integration for Real-Time Data Accuracy: Integration with the ERP system enables dynamic, real-time communication, eliminating double entries and reducing potential errors in production data.

• Enhanced Flexibility: Real-time scheduling optimized for CNC constraints (e.g., tool changeovers, machine availability) enables rapid adjustments to material delays or rush orders.
• Synchronized Production: The system aligns production with raw material deliveries and maintains optimal semi-finished product stocks to meet customer orders.
• Extended Planning Horizon: Planning now covers three weeks instead of one, improving resource utilization through strategies like programming alternative CNC lines.
• Improved Communication: The reliance on physical “sticky” notes has been replaced by Skody’s integrated messaging system, allowing operators to leave detailed notes for each production run or batch, ensuring seamless information sharing across shifts and management.

A Testimonial from Leadership

“Skody AI APS has revolutionized our scheduling, giving us unmatched flexibility with our customers. We no longer need to lock in schedules for four weeks, telling clients, ‘We’d love to take your order, but you’ll have to wait due to fixed lead times.’ With Skody, we’ve extended our planning horizon to one year and drastically reduced the schedule freeze period, enabling us to respond dynamically to customer needs.” — Ken Frenkel, CEO of Three Sigma Technologies (Kent, WA)

Key Outcomes

• 15% reduction in production delays
• Scheduling time reduced from 3–4 days to tens of seconds
• Planning horizon extended from 1 week to 1 year
• Increased efficiency in resource utilization