5 Ways Celonis Process Mining Boosts Manufacturing Efficiency

April 30th 2024
Zeb Khan
Practice Lead - Process Intelligence || Intelligent Automation Manager

 

The manufacturing industry thrives on efficiency, constantly seeking ways to optimize production, streamline operations, and minimize costs. However, traditional methods of analyzing processes often fall short, leaving hidden inefficiencies and missed opportunities lurking beneath the surface. 

This is where we see Process Mining emerge as a game-changer, offering a data-driven approach to unveil the "true story" behind the processes that drive a manufacturing focused business and unlock a new level of operational excellence.

Ciklum has partnered with Celonis, pioneers of the Execution Management System (EMS), leveraging cutting-edge technology to intelligently Find, Frame, and Fix bottlenecks in your manufacturing processes.

Common Manufacturing Challenges:

  1. Production inefficiencies: Bottlenecks, rework, and production delays can significantly impact output and profitability.

  2. Supply chain disruptions: Unforeseen events and poor visibility can disrupt material flow and cause production slowdowns.

  3. Inventory mismanagement: Excess or inadequate inventory levels can lead to unnecessary costs and stockouts, respectively.

  4. Commercial inefficiencies: Order processing delays, invoicing errors, and inefficient pricing strategies can hinder revenue generation.

  5. Time to Market: Inefficient processes and ways of working preventing on time delivery for internal commodities and design changes.

  6. Quality Optimisation:  Giving full visibility and a data driven method to help improve time to detect and time to resolution.

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Celonis to the Rescue:

Celonis process mining analyses data generated throughout various manufacturing operations, offering a detailed picture of how tasks and activities are actually executed in real time. This data can then be used to:

  • Identify bottlenecks: Pinpoint specific areas within production lines, supply chains, and other processes that are causing delays and hindering overall efficiency.

  • Predict and prevent disruptions: Analyze historical data to identify patterns and predict potential disruptions in the supply chain, allowing for proactive mitigation strategies. Build in custom rules into your model to trigger automated alerts and workflows as soon as any issue occurs.

  • Optimize inventory management: Gain insights into demand/consumption patterns, understand real supply to fulfillment lead times to improve planning parameters and optimize inventory levels to minimise storage costs and ensure smooth production flows.

  • Identify areas for cost reduction: Analyze data from various departments to uncover hidden costs and identify opportunities for streamlining operations and reducing expenses.

Transforming Specific Manufacturing Processes:

1_engineering Engineering

  • Focus: Improve efficiency across various engineering processes like design, prototyping, and production handoffs.

  • Process Example: Engineering Change Management, Product Lifecycle Management

  • Benefit:

    • Get full visibility of your end-to-end process, intelligently identify inefficiencies and streamline communication between teams.

    • Improve time to market by highlighting the key reasons for slower approval and delivery times.

    • Support management to easily control conformance, effectiveness and efficiency of the implemented process. Allowing for accelerated process standardization across the business. Reducing friction in any future rollouts of the process.

2_supply chain and logistics Supply Chain and Logistics:

  • Focus: Increase supply chain resilience and improve delivery times.

  • Process Example: Order to Delivery, Procurement, Inventory Management

  • Benefit:

    • Get actual supply lead times and iteratively improve planning parameters with your transactional data.

    • Intelligently optimize your inventory management, ensuring proactive stock transfers and reducing excess stock.

    • Analyze supplier performance, identify potential disruptions, and optimize transportation routes to ensure timely delivery of materials.

3_manufacturing Manufacturing

  • Focus: Optimize warehouse processes and improve production efficiency

  • Process Examples: Warehouse Management, Lineside Replenishment, Kitting & Sequencing, Production Planning

  • Benefit:

    • Analyze actual throughput times of production stations in real time to optimize planned production timelines of work centers.

    • Full visibility and automated assignment of replenishments to prevent shortage in production inventory and downtime.

    • Get your actual lead times from your system of record in real time, iteratively feeding your planning parameters and optimizing production planning.

    • Reduce scrap rate and quality failure by alerting teams proactively and connecting with procurement to intelligently order at risk materials.

4_Commercial and Finance Commercial and Finance:

  • Focus: Streamline order processing, improve invoicing accuracy, and optimize pricing strategies.

  • Process Examples: Accounts Payable, Accounts Receivables, Warranty Claims and Retail Technician Assistance

  • Benefit:

    • Analyze order fulfillment data to identify delays, improve invoicing practices, and gain insights for data-driven pricing decisions.

    • AP: Drive On-Time Payments, Maximize Cash Discounts, Increase Productivity and set controls for improved risk and compliance.

    • AR: Understanding the root cause of late payments – from late deliveries to slow invoicing, master data issues or simply bad behaved customers.

    • Retail Technicians Assistance (CS) – Understand the technicians’ journey in real time when raising issues to the business. Reduce multi hop in escalations and improve training to ensure technicians escalation volume is reduced. Increasing customer first time right for issues and reducing warranty costs. 

    • Warranty Claims: Reduce failures in claims consolidation by understanding why they are falling into the error state and decrease the number of failures to improve customer satisfaction and reduce cost.

 5_quality Quality

  •       Focus: Improve process efficiency for Quality projects to support and improve time to detect           and time to resolve customer issues.

  •       Process Example: Customer Issue Detection, Customer Issue Resolution (8D)

  •       Benefit:

o   Have an automated end to end view on how issues turn into projects and which bottlenecks are causing a high time to detect.

o   Improve resolution times by providing a comprehensive governance view which can be customized to intelligently highlight at risk projects, allow for more accurate target setting and alleviate resolution bottlenecks. 

These processes are just scratching the surface of the potential areas process mining can be implemented to help drive your KPIs in the right direction and realize value for the business. By leveraging the power of Celonis, manufacturing companies can gain a comprehensive understanding of their operations, identify hidden inefficiencies, and implement targeted improvements across various departments. This can lead to increased production efficiency, reduced costs, improved supply chain resilience, and ultimately, a competitive edge in the global marketplace. 

By combining data-driven insights with human expertise, manufacturing companies can embark on a journey of continuous improvement, propelling themselves towards a future of operational excellence and profitability.

Celonis Process Mining also has a profound impact on payment processes, enabling companies to optimize transaction speed and reduce costs. By applying its process mining expertise to payment workflows, Celonis helps businesses identify and eliminate inefficiencies, resulting in faster and more reliable transactions. To learn more about how Celonis revolutionizes payment processes, explore our blog on Celonis and Process Mining's Role in Transforming Payments.

Learn more about our use cases here

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