Optibrick

Automatic logistics planning for a large craft business

Why we like showing this case

‘Craftsmanship’ evokes things that are practical, tangible and often close to us. Like a beautiful kitchen, for example, in which you can celebrate a good start into the day. ‘Algorithms’ and ‘physical models’, that sounds abstract, but allowed us to help a large kitchen manufacturer in a very practical way. They were able to leave tedious manual scheduling behind and to make beautiful kitchens for more people in less time with automated planning.

Task and solution

Brickwork Ventures GmbH had already developed a feature-rich digital planning tool: "Optibrick". A chief user of Optibrick, a large Swiss kitchen manufacturer, faces complex, nested logistics chains and challenging management of many different capacities. Planning, if performed manually, is time-consuming and error-prone. Optibrick was therefore to be supplemented with a planning engine.

The algorithms of such a planning engine have high mathematical and logical requirements; therefore Brickwork - itself a competent full stack development company - relied on our experience in algorithms, mathematical and physical models for the development of the new core ingredient to their platform.

Where can physical models help?

Physical models often add value where you might not think of physics at first, but where precise prediction and simulation are required in operational management or finance: Capacity and resource planning, process optimization, risk minimization, decision management and much more.

They are a versatile and effective toolbox, provided you know how to use them. What we particularly like about physical models:
They are easier to interpret and understand than many other statistical or machine learning methods. The "black box" that is often inherent in machine learning and creates distrust against "artificial intelligence" is not present here; instead, we gain a good understanding of the underlying processes. Physical models also provide excellent opportunities for extrapolation beyond the range of given data, allowing us to predict future trends and phenomena.

Where does automated planning pay off?

The leap to automated planning is often smaller and less expensive than you might think, but can significantly increase cost efficiency and customer satisfaction.

When planning processes are complex and involve many variables, dependencies and constraints, automated solutions quickly outperform even years of experience in "human" planning because they objectively process large amounts of data and take complex relationships into account to generate optimized plans. They enable faster response to changing environments and reduce human error, while allowing planning in scenarios. By analyzing planning data, companies can make informed decisions, optimize their business strategies, and gain competitive advantage.

→ Questions or thoughts about physical models or automated planning? Dr. Markus Abel is looking forward to hearing from you.

Interview with Marcel Camporelli