Welcome to "OEE Monthly with Mr. Evocon" – your trusted guide to smart manufacturing!

Greetings, manufacturers! I’m Mr. Evocon, here to bring you monthly insights on OEE, production monitoring, and continuous improvement. You can expect real-world case studies, expert guides, and key industry trends to help you stay ahead and optimize your operations. Let’s work together to drive efficiency and boost OEE!

In this first edition, we'll explore how to create and analyze downtime reports — vital for anyone looking to improve efficiency with data-driven insights. Then, I'll take you through Mars’ digitalization journey in Cape Town to see how they reduced unaccounted downtime to 0% and improved OEE.

And that's not all! I am happy to introduce our "Decoding World-Class OEE" industry report, featuring a benchmark OEE analysis from 50+ countries and 3,500+ machines.

Finally, we'll explore a thought-provoking piece from "The Manufacturer" on the hurdles to AI adoption in manufacturing — and how you can overcome them to future-proof your operations.

How to Create and Analyze a Downtime Report

In manufacturing, time and efficiency are essential. One key component of time management is understanding how long your machines are working and how long they are stopped. A downtime report is critical when examining factory data and ensuring maximum efficiency.

In this article, you'll learn about production downtime, its impact on manufacturing efficiency and how Evocon can help to create and analyze your downtime reports.

Read the article >

How Mars Achieved Full Transparency on the Shop Floor

A few years ago, Mars began modernizing its operations. In the US and Europe, the company turned to using real-time data across its whole supply chain and set ambitious goals to reduce downtime, improve quality, and achieve energy efficiency.

At the time, Jo-Ann Kitshoff was responsible for operations in Mars’ factory in Cape Town, South Africa. She recalls that downtime used to be written on paper and manually transferred to an Excel spreadsheet. According to her calculations, about 30% of downtime was unaccounted for—meaning they did not know what exactly that time was spent on.

Learn how Mars managed to reduce unaccounted downtime to 0% by moving to technology and shifting the culture at the site.

Read the full case study >

[Free Report] Decoding World-Class OEE

Do you want to learn what a world-class OEE score is and what you can do to achieve it?

This is a global benchmark analysis with data from 50+ countries and 3,500+ machines to help you understand how you compare against other companies. To give an example of what’s inside, here's a sneak peek into the average OEE scores by industry:

Download the full report for more on OEE targets, averages, methods, calculations, and real-world case studies.

Download the free report >

The Challenges Preventing AI Adoption in Manufacturing

A recent survey of UK businesses revealed that only around 15% of manufacturing respondents have adopted AI processes, and of those, only 13% intend to use it actively. So, what’s holding the manufacturing industry back, and what needs to happen for AI’s potential to be unlocked on an industry-wide scale?

This article explores the industry's barriers when it comes to adopting AI:

• Lack of trust:?The lack of transparency in the decision-making process of AI technology makes it difficult to validate the outcomes.
• Uncertainty about AI’s practical benefits and the skills gap: Before companies look to adopt AI tools, they need to fully understand the benefits, including the ROI (Return on Investment), which can be unclear. In addition, a combination of specialized training and knowledge in both AI and manufacturing is essential to creating a workforce capable of supporting AI in manufacturing.
• Complex regulations: Complex AI regulations and a lack of awareness about AI policies make it challenging for manufacturers to identify the correct operating standards. As a result, gaining regulatory approval for AI solutions becomes more difficult.

For successful adoption, ethical, secure, transparent, and reliable AI systems are necessary. Frameworks like the Trustworthy AI Framework are being developed to address these challenges, focusing on fairness, transparency, safety, security, and robustness. These frameworks aim to build trust in AI and provide practical solutions to encourage widespread adoption.

Read the full article on "The Manufacturer" >

Thank you for reading the first edition of "OEE Monthly with Mr. Evocon"! I hope you’re leaving with some new ideas to boost efficiency and tackle downtime challenges. Be sure to subscribe to the newsletter for more updates from Evocon and the manufacturing world.

See you in October!