We’ve noticed unauthorized or inaccurate claims of association with us. Only officially employed or contracted individuals are authorized.

EDM Process Optimization: Reducing Scrap & Recovering Profit Margins

Overview

A precision cutting tools SME specializing in Electrical Discharge Machining (EDM) was experiencing a sharp rise in defects, rework, scrap. These issues resulted in 15% cost overruns on recent orders and declining profitability. The underlining cause was the use of unvalidated, non-optimized internal process rules for EDM machining.

AEM Consulting was brought in to scientifically optimize the EDM process, validate correct machining parameters, and restore the client's operational efficiency and profit margins.

The Challenge

The client's primary challenge was the escalating scrap and defect rates across multiple EDM machines. This directly led to increased production costs, longer machining times, and unreliable output quality.

Key issues includes:

Incorrect internal EDM parameter settings, based on assumptions rather than scientific validation
Inconsistent material removal rates, affecting precision and cycle time
High levels of rework and wasted material, driving cost overruns
Lack of specialized EDM expertise, preventing the client from identifying optimal settings
No standardized machining parameters, leading to variation between operators and machines

Continuing with these flawed parameters would have led to further financial losses, unreliable product quality, and diminishing competitiveness.

AEM Investigation & Root Cause Analysis

AEM began performing a detailed diagnostic to scientifically validate the machining issues.

Process Diagnosis & Hypothesis Testing

AEM performed statistical hypothesis testing to confirm that:

The existing EDM settings significantly contributed to defect generation
Variation was originating from incorrect input parameters rather than operator skill or material inconsistencies

This confirmed that the process itself is not human error, was the source of quality issues.

Designed Experiments (DOE) with Orthogonal L9 Array

AEM conducted a structured Design of Experiments (DOE) using Taguchi Orthogonal L9 Array, varying key EDM parameters such as: Pulse ON time, Pulse OFF time, Current, Voltage, and Wire feed/discharge rate

This enabled precise, controlled experimentation to measure the effect of each factor on: Material Removal Rate (MRR), Surface finish, Dimensional accuracy, Defects occurrence

DOE revealed the exact parameter combination that minimized variation and maximized machining performance.

SPC Charts & Process Stability Analysis

AEM used Statistical Process Control (SPC) charts to:

Verify machining stability before and after optimization
Ensure the new parameters reduced special-cause variation
Confirm long-term repeatability and consistency

The post-intervention control charts showed significantly tighter process control and near-zero defect trends.

Validation & Controlled Trials

Multiple validation cycles were run using the optimized parameters to ensure:

Repeatable and predictable EDM output
Sustainable defect reduction
Acceptable surface finish and dimensional accuracy across different tools

This step ensured the new process settings were robust in real operations, not just experimental conditions.

The AEM Solution

AEM deployed a structured, scientific approach to fully optimize the EDM process.

Root Cause Confirmation

Incorrect, unvalidated EDM parameters were confirmed as the primary driver behind scrap, poor accuracy, and long cycle times.

Experimental Optimization

AEM designed and executed a complete DOE framework using the Orthogonal L9 Array, enabling systematic variation and precise measurement of EDM performance.

This allowed the team to determine: Main effects of each parameter, Interaction effects, and Optimal balance between removal rate and quality

Optimum EDM Parameter Set Identified

A precise, validated parameter combination was established for every EDM machine, ensuring: Consistent machining, Maximum removal rates, Minimum surface defects, and Accurate dimensional control.

Implementation, Standardization & Training

AEM rolled out the optimized settings across all machines and implemented:

Standard operating procedures (SOPs)
Operator training for consistent parameter usage
Control plans and SPC monitoring systems to maintain long-term stability

This ensured sustainable adoption and repeatability.

Results & Impact

The optimized EDM process delivered immediate and measurable improvements:

90% reduction in defects and scrap — drastically lowering material wastage
95% reduction in rework and cost losses, fully eliminating the existing 15% cost overrun
Faster machining cycles — substantially higher material removal rates
Improved throughput and delivery speed, increasing production capacity
Higher operational efficiency through stable, predictable, defect-free machining
Optimized energy usage, reducing electricity consumption and operational costs
Standardized, scientifically validated process, ensuring long-term quality and consistency

The transformation reaffirmed the value of replacing trial-and-error machining with data-driven optimization.

Outcome Summary

We delivered a complete scientific overhaul of the client's EDM process using hypothesis testing, DOE with Orthogonal L9 Array, and SPC-based control systems.

By identifying the optimal machining parameters and enforcing process standardization, the client achieved:

Drastic quality improvement
Major cost savings
Higher machining speed and efficiency
Reliable, repeatable output across all machines

This intervention not only restored profitability but created a sustainable process excellence foundation, giving the SME a competitive edge in the precision machining industry.

For expert assistance in process optimization, defect reduction, and enhancing manufacturing efficiency in complex industrial operations, please contact AEM Consultancy.

Previous Case Study

Page updated

Google Sites

Report abuse