#06 Digital Consulting Services

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SIMULATION
BIG DATA/ANALYTICS

Given the outstanding number of Industry 4.0-enabling technologies and the range of solutions currently available on the market, there could be a high risk of going down investment routes with lower return. Against this varied and complex backdrop, we have combined process know-how gained over one hundred years of Danieli’s history, our strong digital expertise and the proven capabilities in defining the innovation programs of our business partners. And we are now supporting our customers along their digital transformation journey by offering specific consulting services covering various areas (digital strategy development, assessment, simulation, human-machine integration and methodology transfer), depths of analysis and dimensions.

Case
History

Who

Who

European leader in high-quality steel, producing 1,100,000 tons of cast ingots, cast blooms, round and forged bars each year for various industries, such as automotive, trucks, earth-moving equipment, bearings, wind, rail, military, oil & gas, nuclear, agricultural and industrial vehicles.

Why

Why

Pursuing its continuous improvement programme, the customer aimed to improve overall plant efficiency, focusing in particular onon reducing operating costs and lead times

This project was specifically catered to meeting the following needs related to the meltshop area: 

  • minimisation of equipment setup time, especially in the casting machines;

know-how formalisation, especially as regards the scheduling of hard and soft constraints, to guarantee the capability of producing high-quality steel under all conditions.

How

How

Implementation of the Q3-MET Advanced Scheduling solution, providing optimised work order sequences by applying “local search” algorithms in order to minimise a defined multi-objective cost function.

The first activity involved collecting and configuring the required basic information in the master data module, such as the plant equipment, possible routings, transportation times, the process time for each equipment and product and the expected energy per ton for each steel grade. Moreover, the operational and technological soft and hard constraints were jointly defined during this phase of the project.

Definition of the objective functions and of the KPIs to be optimised was then of fundamental importance. Objective functions can be combined and tuned through a set of adjustable parameters to calculate the overall costs of the solution. The solution provides the possibility of storing different configurations to support several plant working conditions. Primary information, such as appointments, products, steel grades and quantities, hot-charge appointments, order priorities and quality aspects are examples of factors that can affect the schedule. After collecting the order portfolio and selecting the objective function to apply, the user starts to show the evolution of the schedule in real-time, giving the scheduler an easy-to-understand, clear picture of the plant schedule and the actual cost of the solution. When the total cost of the objective functions cannot be improved any further, the optimisation process is complete.

What

What

The benefits obtained by the customer can be summarised as follows:

  • optimized meltshop efficiency;
  • minimised quality critical paths.

The customer is currently evaluating the possibility of extending this approach to other plant areas.

Who

European leader in high-quality steel, producing 1,100,000 tons of cast ingots, cast blooms, round and forged bars each year for various industries, such as automotive, trucks, earth-moving equipment, bearings, wind, rail, military, oil & gas, nuclear, agricultural and industrial vehicles.

Why

Pursuing its continuous improvement programme, the customer aimed to improve overall plant efficiency, focusing in particular onon reducing operating costs and lead times

This project was specifically catered to meeting the following needs related to the meltshop area: 

  • minimisation of equipment setup time, especially in the casting machines;

know-how formalisation, especially as regards the scheduling of hard and soft constraints, to guarantee the capability of producing high-quality steel under all conditions.

How

Implementation of the Q3-MET Advanced Scheduling solution, providing optimised work order sequences by applying “local search” algorithms in order to minimise a defined multi-objective cost function.

The first activity involved collecting and configuring the required basic information in the master data module, such as the plant equipment, possible routings, transportation times, the process time for each equipment and product and the expected energy per ton for each steel grade. Moreover, the operational and technological soft and hard constraints were jointly defined during this phase of the project.

Definition of the objective functions and of the KPIs to be optimised was then of fundamental importance. Objective functions can be combined and tuned through a set of adjustable parameters to calculate the overall costs of the solution. The solution provides the possibility of storing different configurations to support several plant working conditions. Primary information, such as appointments, products, steel grades and quantities, hot-charge appointments, order priorities and quality aspects are examples of factors that can affect the schedule. After collecting the order portfolio and selecting the objective function to apply, the user starts to show the evolution of the schedule in real-time, giving the scheduler an easy-to-understand, clear picture of the plant schedule and the actual cost of the solution. When the total cost of the objective functions cannot be improved any further, the optimisation process is complete.

What

The benefits obtained by the customer can be summarised as follows:

  • optimized meltshop efficiency;
  • minimised quality critical paths.

The customer is currently evaluating the possibility of extending this approach to other plant areas.