Our client, a Small and Medium Enterprise (SME) specializing in cutting tools manufacturing, produces high-density tools primarily for lathe machining operations such as turning, facing, and cutting. Given the extreme hardness of these materials, the client relies on Electrical Discharge Machining (EDM) to precisely shape their tools, circumventing the limitations of traditional manufacturing methods. Operating on a make-to-order basis, the client found themselves in a challenging situation, facing consistent losses from increased scrap and defect rates over their last five orders. These issues led to a 15% cost overrun compared to their initial quotations, significantly impacting profitability. As an SME, the client lacked expertise in process optimization, relying instead on internally developed, unvalidated manufacturing rules. Recognizing the urgent need for intervention, the client engaged AEM Consulting to reduce defects and scrap, optimize their production process, and enhance overall efficiency.

The core challenge faced by the client was a significant increase in scrap and defect rates during the EDM process, leading to a substantial 15% cost overrun on recent orders. This issue stemmed from their reliance on internally set, non-optimized process parameters for machining high-density tool materials. The use of these suboptimal parameters resulted in inconsistent and inefficient material removal rates, directly contributing to product defects and unmanageable scrap. As an SME, the client lacked the specialized knowledge and resources to identify and implement optimized EDM parameters, creating a critical bottleneck in their production efficiency and profitability.

AEM Consulting initiated a collaborative, cross-functional approach, working closely with the client's team to address the identified root cause: the use of incorrect internal process parameters. Our solution focused on a scientific, experimental approach to determine optimal EDM settings:

1. Root Cause Identification: Through initial analysis, it was definitively established that the varying and often suboptimal material removal rates, leading to defects and scrap, were a direct consequence of the client's internally set, unoptimized EDM process parameters.

2. Experimental Design and Optimization: AEM's experts, working alongside the client's operators and engineers, designed and executed a series of controlled experiments. These experiments systematically varied critical EDM process parameters to understand their impact on material removal rates and tool quality.

3. Optimum Parameter Determination: Through rigorous testing and analysis, the optimal process parameters were precisely identified for each specific EDM machine. These parameters were designed to maximize the material removal rate while ensuring the highest quality output, free from defects and scrap.

4. Process Implementation and Standardization: The newly determined optimum parameters were meticulously implemented and standardized across all relevant EDM machines. Operators were trained on these new settings to ensure consistent application and uniform machining performance.

The implementation of optimized EDM process parameters yielded immediate and highly significant improvements for the client:

• Dramatic Reduction in Defects and Scrap: The overall defect and scrap rates were reduced by an impressive 90%. This direct impact led to a substantial decrease in material waste and eliminated the need for costly reworks.

• Significant Reduction in Rework and Losses: Consequently, rework requirements and the associated company losses were slashed by 95%. This directly addressed the 15% cost overrun issue, transforming a previously loss-making scenario into a profitable one.

• Maximized Material Removal Rate: The optimized parameters ensured the highest possible material removal rate for the client's specific high-density materials, leading to faster machining cycles and increased throughput.

• Enhanced Operational Efficiency: The uniform and defect-free machining process significantly improved overall operational efficiency.

• Optimized Electricity Utility: An unexpected but significant additional benefit observed was the optimum utilization of electricity during the machining process. This indicates that the optimized parameters not only improved material outcomes but also contributed to energy efficiency, leading to further cost savings (specific details of process parameters remain confidential to protect client data).

These results underscore the profound impact of data-driven process optimization on manufacturing efficiency, cost reduction, and overall business performance, particularly for SMEs.