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Improved throughput by 23% compared to the baseline
Plant availability improved by 20%
Work-in-progress days reduced by 40%
Aluminum circles manufacturing in India is a well-established industry catering to diverse sectors such as die casting, flange manufacturing, automotive, electrical, and electronics. Indian manufacturers produce aluminum circles in various sizes (typically from 4 inches to over 28 inches in diameter) and thicknesses (ranging from 0.7 mm to over 6 mm), using different aluminum grades.
The Indian aluminum industry, which includes primary aluminum, extrusions, rolled products, and downstream items like aluminum circles, is projected to grow at a CAGR of around 6.7% through 2026-27, with aluminum consumption expected to reach approximately 4.84 million tonnes by then. However, this sector has its own set of challenges.
The client is an India-based manufacturer of quality-grade aluminum circles. The company produces aluminum products used by well-known cookware brands and boasts in-house quality control and R&D capabilities.
The client was facing issues with inefficient throughput, high levels of unplanned downtime, poor visibility in order fulfillment, and underutilized manpower, which resulted in their partnership with Consulting.
The project was undertaken with the primary objectives of improving throughput, reducing repetitive failures, and designing and installing operational scorecards. The joint the client team identified several issues that were undermining the client’s performance. These included:
Observational studies highlighted managerial control and problem-solving opportunities from the operator level up to the production in-charge level.
The client elected to deploy Consulting Focus Process® to develop a broad understanding of the opportunities and promote engagement in changes to processes and management systems.
The joint team from the client and Consulting conducted focused discussions with key process owners, supported by observational studies, to identify daily operational challenges.
The approach involved implementing checks and controls as system elements to guide behaviors towards achieving the desired output level. To minimize unplanned downtime, the focus was on improving OTIF (on-time in full) through better production planning, a more rigorous preventive maintenance (PM) schedule, real-time monitoring of downtime at hourly intervals, and effective spares planning.
Trials were conducted to test solutions for recurring issues, and planned downtime was reduced through advanced casting planning during Sales Inventory Operations Planning (SIOP) meetings. This improved the visibility of orders, enabling better resource allocation and enhancing manpower productivity for more effective resource utilization. A cross-functional Management Action Team (MAT), consisting of representatives from all key functions, was formed to ensure active participation and effective management of the initiative.
Several system elements were introduced to address issues related to order planning and sequencing. First, a formal review structure was established to assess performance and plan for the upcoming period.
To improve shop floor performance, machine-wise performance boards were installed, encouraging a culture of short interval control.
To enable real-time decision-making, tools for WIP inventory tracking and order tracking were implemented, alongside daily and weekly KPI dashboards and sales order dispatch dashboards.
The entire process, from sales order through production scheduling and dispatch, was integrated into a Sales Inventory and Operations Planning (SIOP) ecosystem. This system, supported by strong review mechanisms, manages critical elements, such as raw material requirements and production lot sequencing, which ultimately resulted in improved OTIF (on time in full) performance.
Additionally, a pull-based production system was introduced, and an end-to-end aluminum recovery tracking mechanism was implemented, allowing the client to track losses at every stage of production. This helped improve yield by 2%, leading to better process efficiency.
The transformation led to substantial gains across all critical performance areas:
*Client-specific details have been intentionally omitted to maintain strict discretion.
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