AI powering smarter factories

Sogeti, in collaboration with Husqvarna and Microsoft, delivered a scalable infrastructure supporting multiple factories, enabling cloud-based management and edge computing. The initiative included change management and user involvement, resulting in Gen AI solutions for factory shutdowns, improved OEE reporting, and better data through misclassification support.

Husqvarna, founded in 1689, is a company with a rich history and a strong passion for innovation. It manufactures professional products for forestry, parks, and gardens, combining high performance and user-friendliness with safety and environmental care.

A leader in battery solutions and robotics, Husqvarna has evolved from producing guns to sewing machines, stoves, motorcycles, and now cutting-edge outdoor equipment. Headquartered in Huskvarna, Sweden, the company operates globally with sales offices supporting its international customer base.

Background

Husqvarna, a global manufacturer of robots, chainsaws, construction equipment, and garden tools, has made significant investments in equipment, workforce, and infrastructure.

Husqvarna Manufacturing IT works closely with business operations and factories to ensure high utilization rates and operational efficiency, helping the company stay competitive in a rapidly evolving market. Sogeti is proud to partner with Husqvarna in unifying infrastructure and developing use cases aimed at maximizing overall equipment efficiency across 30+ factories, 100+ countries, and three divisions.

Solution

Way of Working – Husqvarna, Sogeti, and Microsoft collaborate as a unified team, aligning strategy, technology, and business value in parallel. Sogeti refers to this approach as a “core team,” which enables faster time-to-value and reduced risk.

Architecture, Infrastructure, and Platform – By combining Sogeti’s expertise in Azure, infrastructure, cloud, data, and AI with Husqvarna’s domain knowledge, the team has established best practices and reference architecture for IoT operations, data flows using Azure Databricks, and standardized data models.

Use Case Realization – Starting with known value-generating cases and involving users early, the team demonstrates the benefits of implemented solutions and creates synergies for new use cases. This approach ensures profitability and maximizes the return on investment.

Result

The outcomes are continuously evolving, but have already led to several production-ready solutions built on an infrastructure and platform that support multiple factories. This includes cloud-based management of connected IT/OT environments and the ability to run containerized applications at the edge.

Key results include a Gen AI solution to address factory stoppages, initial OEE reporting through new data flows, and a misclassification solution that improves data quality—ultimately enhancing OEE and enabling further use cases. One clear example of value is the reduction in stoppages, where the Gen AI solution is considered cost-effective after preventing just 1–2 stoppages, which occur multiple times annually across various factories.