Services

Production

This is the era of ultra-rapid change and ever-increasing complexity in Production. Utilize Process Mining and cut costs, guarantee quality, and minimize scrap while satisfying customer demand

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0%
increase

of adherence to schedule

0%
reduction

of waste


Unlock Your Full Potential in Production

It is important to know when a production order will be completed or how quickly a new production order can be started. That is why Processand ensures complete process transparency in production, so you could make proactive decisions. By utilizing Process Mining, identify and remove execution gaps that get in the way of accurate production planning, seamless assembly lines, and optimal machine utilization. Don’t wait around, make value driven decisions and become the market leader.

How we help

Processand’s expertise ensures business process optimization and immediate value generation in production

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Processand Use Cases

Swipe for processes

Production Planning​
Inventory Management
Extended Warehouse Management

Adherence to Schedule and Quantity​

inefficiency / challenge

  • Deviations between the planned and actual start date, end date and quantity are common in the production process.
  • Quantity drop across several production steps.
  • Deviatons to schedule hinder accurate production planning and leads to a deterioration in delivery reliability as well as distortions in supply chains​

solution and targeted outcome

  • Implement an analysis to create transparency on adherence to schedule and deviations between target and actual production start and end dates.
  • Implement an analysis on quantity adherence and deviations between different production steps.
  • Investigate all cases in detail where deviations from the target date occur.
  • Optimize planning quality and increase working capital.​ ​

business objectives

  • Operational Cost Reduction
  • Ensure Quality
  • Mitigate Risk​

core KPIs

  • Adherence to Schedule
  • Adherence to Quantity​

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Waste Reduction

inefficiency / challenge

  • Wasted materials cause costs without any benefit.
  • Often the actual share of material waste is significantly higher than planned.
  • Companies lack accurate overview of their material waste.

solution and targeted outcome

  • Monitor your material waste in real time.
  • Find bottlenecks in your production process.
  • Apply analyses to identify problem drivers and execute targeted action to minimize your material waste.

business objectives

  • Operational Cost Reduction

core KPIs

  • % Actual Good Quantity
  • % Planned Good Quantity
  • % Material Waste

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Target vs. Actual Operation Times

inefficiency / challenge

  • Deviations in target and actual time at the operational level.
  • Creating and evaluating a transparent analysis of the target/actual times at the operational level.

solution and targeted outcome

  • The analysis provides a target/actual comparison of such times.
  • Investigate time, costs, process flow, etc. of operations.
  • Monitor and analyze root causes of deviations.

business objectives

  • Spend Optimization
  • Labor Productivity

core KPIs

  • Target Time of Operation
  • Actual Time of Operation
  • Absolute Deviation

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Shopload Planning

inefficiency / challenge

  • A lack of transparency on how many production orders have been produced, booked, planned and delivered.
  • Inefficiencies in production planning as well as suboptimal utilization of production capacities.

solution and targeted outcome

  • Detailed overview of the number of delivered, produced and booked production orders over time.
  • Real-time tracking ensures that the production plan is adhered, and that production capacity is optimally utilized.

business objectives

  • Spend Optimization

core KPIs

  • # Delivered
  • # Booked
  • # Produced

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Incorrect Production Orders

inefficiency / challenge

  • Production orders may not always contain the correct quantity of every component and sometimes even incorrect components may be included.
  • This might be due to wrong object dependencies, errors in BOMs, mistakes in order picking or wrongly provided material by the supplier.

solution and targeted outcome

  • Process Mining creates transparency about change activities in production orders.
  • It enables you to analyse root causes of back-posted orders and the business impact based on manual effort and its costs.

business objectives

  • Operational Cost Reduction
  • Labor Productivity

core KPIs

  • # of Back-Posted Orders
  • # of Back Postings
  • Total Back-Posted Value

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Inventory Correction Activities

inefficiency / challenge

  • Inventory corrections cause unnecessary manual efforts.
  • Failures in the bill of material (BOM).
  • Lack of transparency during the ramp up / ramp down phases and manual activities in the picking process.

solution and targeted outcome

  • Display quantity, materials and time effort of inventory posting activities.
  • Track potential monetary savings by quantifying costs for these activities.
  • Analyze causes based on time, plants, materials and material movements.

business objectives

  • Spend Reduction
  • Labor Productivity

core KPIs

  • Effort of Corrections
  • Potential Savings

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Stockout Mitigation

inefficiency / challenge

  • Volatile demand and inefficiencies in underlying processes (e.g., cancellations) pose non-forecastable risk & potential stockouts.
  • Limited visibility and manual assessment of inventory levels increases risk of potential stockouts.
  • Identifying critical materials, where stock needs to be present to fulfill demand is critical to ensure high customer satisfaction and not miss out on revenue

solution and targeted outcome

  • Monitor the actual performance and have visibility over underlying process of your supply.
  • Detect risk in your inventory coverage based on inefficiencies.
  • Align your stock planning parameters with the behavior of your supply: delivery capacities and lead times
  • Track incoming orders & need for replenishment. Receive intelligent alerts for stockout risk due to demand fluctuations based on historical data.

business objectives

  • Spend Reduction
  • Labor Productivity

core KPIs

  • Potential Savings

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Delivery Delay Prediction

inefficiency / challenge

  • Deliveries arrive at the warehouse too early or too late.
  • Inefficiencies within warehouse management due to clarification effort.
  • Inefficiencies in the production pipeline due to material non-availability.

solution and targeted outcome

  • Machine Learning algorithm for delivery delay prediction.
  • Real-time monitoring of delivery delays to target on-time delivery.
  • Automating the notification of stakeholders involved.

business objectives

  • Supply Reliability Production
  • Planning Improvement
  • Working Capital

core KPIs

  • Early Recognition of Supply Chain Issues
  • Automatic Root-Cause Analysis of Delays (beta)

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Learn More About Process Mining.

GET IN TOUCH

Begin Your Process Mining Implementation

With over 350 process implementations, we know exactly what the crucial parts of a successful Process Mining initiative are

Patrick Bogner

Data Science Team Lead

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