Knar Learning

Training on Performance Modeling, Forecasting and Improvement - Industrial Assets

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What are the benefits for attendees?

Improve the effectiveness for managing Industrial Asset by increasing the correctness and agility for decision-making.

Attendees will learn how to use and deploy decision making infrastructure, as models, forecasts, and Digital Assets,  and will learn how to use such analytical infrastructure to assess technical alternatives in the context of complete, comprehensive and complex business scenarios.

The approach: 

Decision making infrastructure is a must for complex industrial assets

Training starts challenging a common fact. Industrial organizations have hundreds or event thousands of equipments for processing mass and energy, but lack of the most basic elements for enabling precise, timely and correct decision-making processes apt to manage demands imposed by market and general business dynamics.

The training explains how to develop and use such infrastructure to generate business value. 

Training on Performance Modeling, Forecasting and Improvement - Industrial Assets

  1. Decision-making and Business Value.
  2. The past: Round-table debates and anecdotic appraisals
  3. Forecast-based decision-making. Advantages, limitations and long term effects.
  4. Business Context: External performance drivers and perturbations
  5. Industrial Asset: Internal performance drivers and perturbations.
  6. Physical Asset, Digital Assets and Decision Making
    • Modeling and Simulation of Business Context Dynamics 
    • Prices, Demand, Competition.
    • Environmental influences. 
    • Digital assets and the mind of the asset.
  8. Complexity on Decision Making
    • Variability
    • Interconnectedness
    • Randomness
    • Uncertainty
  9. Modeling and Simulation inside Industrial Asset
    • Flows, Processing Units, Configurations and Capacities.
    • Operational Modes, Operational Logic, Operability.
    • Reliability, Maintainability and Maintenance.
    • Production & Maintenance Logistics. 
  10. Decision-making
    • Representing business scenarios and decision-making context
    • Representing Alternatives to asses in the Industrial Assets.
    • Value-losses allocation
    • Plant performance optimization. 
  11. . Application Examples
    • Balancing Plant Configuration, CAPEX (Investment) , OPEX and REX.
    • Equipment obsolescence. When to replace assets.
    • Maintenance Strategy Assessment.
    • Defining scope and manning on Service Contracts.
    • Energy and Efficiency Analysis
  12. Closure
    • Decision-making ecosystem.
    • Digital Asset Implementation Roadmap

Interested?...Reach us using the left pane, and let's talk on how to develop the competencies of your team on 21st century decision making tools

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