PSI Blog

The Synthesis of Autonomous and Adaptive Scheduling - Smart Agents for Smart Production Planning

06 Oct 2021 - Research, Industry 4.0, Production, Sustainability, Technology, Artificial Intelligence

©Daniel Lazaj/iStock; edited by PSI Metals

Production planning is one of the most complex industrial challenges of the steel industry - it is roughly equivalent to the complexity of a Petri net with up to one million nodes! To address this complexity, metals manufacturers have developed several IT solutions and business processes. However, in addition to complexity, the production process is systematically affected by unpredictable events. In most plants today, responding to production disruptions is a human decision made by operators - often leading to response time issues that can cause production downtime and additional costs. The smart agent technology provides a remedy.

Only some plant events, interactions, and decisions related to a few hours of the scheduling of casters and HSM ©chokja/iStock; edited by PSI Metals

Steel production scheduling is a very complex business process that requires a complex collaborative solution. It involves different stakeholders, with common but also contradicting goals, such as:

  • Keeping equipment busy and running
  • Deliver finished goods in time, but don’t produce too early or too late
  • Keep intermediate and finished stocks low but make sure you have enough

This makes production scheduling in the steel industry considerably one of the most difficult and complex industrial planning and scheduling problems. It involves several sequential production steps for each finished  product, each step transforming the semi-finished material and needing different, often alternative, resources, transport, and warehouse systems (e.g. cranes, forklifts, piles). Furthermore, each step needs to fulfil critical, and sometimes opposing, production constraints.

Fighting the Complexity of Production Planning

To combat this complexity, metal producers have developed IT solutions and business processes. The efforts to meet the complexity are typically organized in a hierarchical decision workflow:

  • Capacity planning
  • Material allocation and combination planning
  • Cross line campaign and production scheduling
  • Detailed production line scheduling
  • Transport planning
  • Reactive schedule execution

This workflow is managed by many human operators such as capacity & material planners, line schedulers, production line operators, crane & transport drivers, warehouse managers, etc.

These human decision makers use software applications to help them make required decisions.

People – Planning Teammates in Your Supply Chain © PSI Metals

Besides the complexity of the production process itself, this production process is systematically affected by unpredictable events, such as equipment breakdowns, campaign restrictions, orders cancellations or changes, energy demand limitations, material unit unavailability, mechanical and chemical property misses. In most of today’s plants, reacting to and deciding on such disturbances is a human decision made by the operators; they have to detect the disturbance, analyze the possible impact and decide on corrective actions and communications as seen in our Stark Inc example aboce.

These human decision points, however, have some problems with reaction latency: Some operators are only available during office hours, people are not always focused and in general, humans are rather slow - the reaction time to disturbances could be minutes to hours.

The problem is that lagged or omitted disturbance handling can lead to production failures and extra cost. With smart agent technology, we can counter this. 

Phases of reaction to an unexpected event © PSI Metals

Smart Agents Can Improve All Parts of the Reaction to Unplanned Events

Smart agents are small pieces of software focused on a very specific set of problems. They can automatically react  to a wide variety of data sources and are capable of synthesizing a multitude of data inputs and assessing the impact of changes.

Smart agents are autonomous decision makers and can make independent, local decisions.

Like human beings, they can solve larger problems by communicating with other agents in so-called Multi-Agent Systems (MAS). We believe that smart agents can improve all parts of the reaction to unplanned events.

Imagine that smart agents could execute the following tasks:

  • Tracking events related to each production order
  • Observing the output quality of the casting of rolling process, triggering alarms if needed
  • Observing the feasibility of a released caster or HSM schedule and triggering delays or rescheduling when needed 24/7
  • Handling rescheduling and propagating the consequences to other smart agents 
  • Observing material movements to verify material availability requirements
Smart Agents © PSI Metals

In this world, everyday life at the Stark Inc. flat steel plant in Massachusetts would look different:

©chokja/iStock; edited by PSI Metals

Do you want to know how PSImetals Planning can help you improve your supply chain sustainability?

Leave the road, take the trails and join us in exploring the nature of your supply chain! Follow our “Explore the Nature of Your Supply Chain - Smart Plans for Sustainable Metals Production” campaign, which is enriched with many exciting blog articles and exclusive webinars!

Luc Van Nerom

Deputy Managing Director PSI Metals 

After studying mathematics and computer science, he founded Artificial Intelligence Systems in 1986. The mission was to bring AI technology to the energy and process industry. Especially in the metals industry this crystalized into a number of production management optimizers today fully embedded into the PSI Metals portfolio. Nowadays at PSI, he focusses on innovation and product management. He is also managing director of PSI Metals Belgium.