Digital Manufacturing

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.

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 is the use of connected machines, real-time data and software to run a factory on facts rather than assumptions. Here is what it means for a plant with existing equipment, and where to start.

Real-time analytics can revolutionize decision-making providing immediate valuable insights to drive strategic actions. From optimizing timing for analytics to fostering seamless data sharing across organizational boundaries, uncover the key strategies for success in leveraging real-time insights. Don’t miss out on unlocking the potential of real-time analytics to streamline operations and gain a competitive advantage. Introduction […]

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.

You don’t have to replace your machines with the new ones to make your production „smarter” and more efficient. Your shop floor is a data mine, and digitization is the key to unlock its value.

Very often overlooked or accepted as-is due to being an integral part of the production – in times of crisis and cost-cutting, it can become a major factor that improves the bottom line of your organization. Where to look for significant energy savings to reduce energy costs? How manufacturers should focus on these goals to make an impact? 

According to the German Federal Statistical Office, energy consumption by the industry for the production of goods hardly changed between 1995 and 2019. In 2019, it amounted to 3,874 petajoules. This means that it remains at the same level as in previous years. Germany plans to halve its primary consumption of energy by 2050, with the industry having to take part. In the era of the energy crisis, the drive to improve corporate energy efficiency is entering a new level.

In the manufacturing industry, efficiency is key to staying competitive and profitable. One way to improve efficiency is through data visibility. By having access to real-time visibility of the operational data throughout the manufacturing process, companies can identify bottlenecks, monitor production lines, and make data-driven decisions. In this article, we’ll explore how data visibility can help manufacturing companies improve their efficiency and ultimately their bottom line.

We are all blessed to live in very exciting times. Exponential technological progress over the last couple of decades has influenced not only our personal lives but also heavily impacted business. Trends are obviously evolving occasionally, but it is safe to say that now is the time of advanced analytics.

Discover the game-changing power of predictive maintenance! Forbes and numerous reports agree that it’s a must-know trend for Industry 4.0 in 2022. Imagine having advanced analytics and AI-based forecasting at your fingertips, enabling you to prevent costly breakdowns and optimize your manufacturing processes.