Internet of Things

Industrial data is growing faster than most manufacturers can process — yet much of its potential remains locked inside disconnected systems, legacy integrations, and outdated architectures. As a result, critical insights arrive too late, operational decisions lose accuracy, and digital initiatives struggle to scale. This article explains why traditional data management can no longer support modern industrial needs and how a Unified Namespace approach helps eliminate silos, unify data flows, and create the real-time foundation required for Industry 4.0, advanced analytics, OEE optimization, and energy efficiency.

Choosing the right OEE (Overall Equipment Efficiency) system is crucial for optimizing production performance. In this article, we highlight the key factors to consider when selecting an OEE system to effectively monitor machine efficiency, minimize downtime, and improve production quality. Learn how to choose a system that supports your factory’s growth and delivers real, measurable benefits.

In the fast-paced aviation and defense industry, one of our clients faced a key challenge: how to accelerate the adoption of modern technologies and maintain competitiveness. The solution? Implementing a Continuous Innovation Program as the foundation of a new business model. A crucial aspect of this program was the continuous testing of state-of-the-art technologies to bring increasingly innovative products to market.

A pharmaceutical company aimed to enhance its innovation by actively testing modern technologies. A key challenge was skillfully and effectively integrating technological innovations into the production area so that data could be collected and analyzed in real-time. The company wanted to show that it is in the „close peloton” of digitalization of production, thereby increasing its market competitiveness.

A company in the electronics industry specializing in semiconductor manufacturing set a major goal to make improvements that positively affect the quality of final products. A key element was to monitor and identify correlations that would predict the satisfactory quality of products coming off the production line. This was done using data from machines and quality control stations, which was then subjected to in-depth analysis. This enabled the company to better understand which factors affect the quality of their products.

An automotive company needed a solution to monitor production to improve the quality of final products. The key element was identifying issues by analyzing quality data correlated with production data. Special attention was given to the casting and cooling zones, where product quality was particularly variable.

A global company in the electrical accessories manufacturing industry used in automation faced the challenge of improving key performance indicators (KPIs), particularly increasing the availability and efficiency of production cells. Each workstation involved multiple stages of assembly and production across various positions and locations, requiring a coordinated approach to managing work, materials, and proper planning.

A client, a leader in the glass packaging manufacturing sector, identified the need to implement an integrated production data management system to replace outdated, manual reporting methods.

Introduction In the highly competitive food and beverage industry, achieving optimal Key Performance Indicators (KPIs) such as availability, performance, and quality is essential for maximizing operational efficiency and profitability. A client operating semi-automated production lines was experiencing persistent underperformance in these KPIs. To address this issue, the company required a robust and precise data-driven approach […]

In the aerospace and defense industry, which is characterized by particularly high requirements for precision and reliability, key performance indicators in maintenance, failure prediction or machine condition monitoring, are crucial.

Industry 4.0, also referred to as the fourth industrial revolution, is a concept encompassing a complex process of technological and organizational transformation of companies, which began in 2013.

If you think OEE has no secrets to you and your plant maintain highest OEE results… think again. Harsh truth is that most manufacturing plants’ OEE land somewhere between 35 and 43%. They just don’t know about that.