What happens to your production when the power flickers, a server reboots at the wrong moment or a firewall rule opens a door you did not know existed?

In this episode, Erik Søndergaard joins The Food Tech Podcast to unpack operational resilience in food and beverage production. From power drops and UPS age to backups, segmentation and NIS2, Erik explains how to think about uptime like an insurance policy: decide what an hour of lost production costs, then secure your systems to match that risk.

If you run a dairy, brewery or any process plant, you will hear concrete steps to keep lines running and systems ready to restart safely when something goes wrong.

In this episode, you will learn:

1. What operational resilience really means on the factory floor

2. Why power disturbances and aging UPS units are still the biggest real-world risks

3. How to use redundancy, backups and restore tests to protect critical servers

4. How network segmentation and OT/IT separation limit the blast radius of an attack

5. Why NIS2 is not just paperwork but a catalog of good uptime practices

Episode Content

00:06 What operational resilience means in a digitized production

01:34 Real-world blockers of production and why power is enemy number one

03:38 IT vs OT - why five minutes offline is different in an office than in a cheese vat

05:44 Defining operational resilience as the ability to keep producing and restart safely

09:04 Calculating the cost of downtime and using risk analysis as an insurance model

11:20 Legacy equipment, isolation and why “air gaps” still matter for old systems

13:13 Why security is never “done” and the need for regular hygiene walk-throughs

16:05 The firewall rule that opened everything and what it teaches about everyday shortcuts

20:42 How segmentation limits the blast radius when something does go wrong

22:35 The basics to fix first - UPS age, server redundancy, backups and restore tests

26:23 Thinking in fire doors and zones for OT networks and systems

27:48 Securing vendor remote access without importing new risks

30:53 Clear roles when something breaks and anchoring responsibility at board level

33:31 Treating NIS2 as uptime engineering instead of box-ticking compliance

This podcast is brought to you by Au2mate.

This podcast is produced by Montanus.

AI is everywhere, but turning it into real outcomes in dairy and food processing is where the value is. In this episode, Anna Olsson, co-founder of Intelecy (a no-code platform for industrial AI), cuts through the hype to show what plants can do today: predict failures before they happen, optimize processes in real time, and capture expert know-how so it scales across sites.

If you run operations, engineering, maintenance, or production IT, you will get practical steps to start fast, prove ROI, and avoid pilot purgatory.

In this episode, you’ll discover:

1. The “learn, act, detect” framework for industrial AI

2. Why data quality and coverage beat big promises

3. How to move from pilots to scaled, maintained models

4. Where predictive maintenance ends and process optimization begins

5. How no-code tools bridge the IT–OT gap and protect operator trust

Episode Content

01:57 After ChatGPT – expectations vs industrial reality

03:06 LLMs vs industrial AI and time-series sensor data

04:47 The “learn, act, detect” framework for process optimization

05:26 Predictive maintenance in practice and planning stops instead of reacting

06:40 Predicting future process states and adjusting before quality drifts

10:23 Tacit know-how and “knocking on pumps” vs data-driven models

12:21 Prerequisites for AI: stored sensor data and data quality

15:20 Case: how TINE detects bacterial contamination with AI

17:28 Energy optimization and small savings that add up 24/7

19:37 Why AI projects fail and end up in “pilot purgatory”

21:02 Build vs buy – scaling beyond the first AI model

31:25 Towards Industry 4.0 – closing the loop from prediction to automation

This podcast is brought to you by Au2mate.This podcast is produced by Montanus.

How important is data in modern dairy production, and how do you turn it into real outcomes on the factory floor?

In this episode, we talk with Erik Vedfald, Chief Architect for Production IT at Arla. Erik explains why quality beats quantity in data and what it takes to move from proofs of concept to trusted tools operators actually use. We discuss sensors, governance, UX and the long game of preparing today’s datasets for tomorrow’s analytics and AI.

If you work in operations, engineering or production IT, you will get practical guidance on where to start, how to involve your teams, and of course, how to avoid the common pitfalls.

In this episode, you’ll discover:

1. Why data quality matters more than having lots of data

2. How to pick high-impact use cases that pay back

3. Ways to structure “data zones” and connect them with a digital thread

4. How to earn operator trust and avoid AI “first-try” failures

5. Practical steps medium-sized dairies can take to get started

Episode content

01:18 Why “keeping up to speed” in production is an illusion

03:55 Are dairies slow or simply paced by ROI and business cases

06:12 Why you can’t just drop AI on raw production data

07:36 Sensors and “dumb vs. deep” data that actually matter

09:21 The skeleton and digital thread analogy for connecting data

10:33 Building high-quality “data zones,” starting at milk intake

11:47 Adoption challenges: UX, change management, and operator workflows

14:50 Data governance and the three-year horizon for training models

16:58 Trust is fragile: the high cost of early bad AI answers

26:37 Bottom-up innovation and scaling local wins across sites

Production

This podcast is brought to you by Au2mate.This podcast is produced by Montanus.

How can tweaking milk fat content by just 0.15% unlock huge savings – even for smaller dairies?

This week, we sit down with Michael Sievers from FOSS, who has spent three decades shaping the future of dairy automation. He reveals how FOSS inline sensors now measure around 80% of the world’s milk, and also how that data helps dairies boost yield, cut waste, and put real money back in the business.

Whether you run a small creamery or a mid-sized dairy, you’ll hear how precision and automation can help you save on raw materials, ride out volatile market prices, and stay competitive against the big players.

In this episode, you’ll discover:

1. How inline sensors turn raw milk data into efficiency gains.

2. Why real-time analysis is a game-changer for dairies of every size.

3. How automation drives higher yield and lower costs.

4. The surprising bottom-line impact of tiny fat adjustments.

5. How Industry 4.0 is reshaping the dairy industry.

Episode Content

01:53 Importance of Production Optimization in Dairy

04:33 Real-time Process Monitoring for Medium-sized Dairies

05:18 Practical Examples: Butter and Milk Fat Optimization

10:06 Financial Benefits of Automation for Smaller Dairies

12:30 Supply Chain Dynamics: Fat and Protein Utilization

14:19 Selling Excess Cream to Larger Dairies

17:45 Steps to Implement Inline Automation Systems

22:30 Overcoming Resistance to Technological Change in Dairies

27:18 Future Trends: AI and Inline Measurement Integration

Production

This podcast is brought to you by Au2mate.

This podcast is produced by Montanus.

How can medium-sized dairies extract more value from every liter of raw milk?

In this episode, we talk with Jesper Kjeldal, Sales Director at MMS Nordic and a specialist in membrane filtration. He explains how modern separation technologies not only reduce waste but also open up new opportunities to tailor the composition of milk, including lactose, minerals, and proteins, to specific products and customer demands.

If you work in operations, engineering, or production in the dairy industry, you will find practical insights here you can apply in your daily work.

Tune in for inspiration on how even smaller dairies can take the next technological step.

In this episode, you’ll learn:

1. How membrane filtration maximizes the value of raw milk

2. The key differences between ultra, micro, and nano filtration

3. Emerging whey processing trends and their profit potential

4. How efficient separation techniques improve sustainability

5. What challenges and innovations lie ahead for the dairy industry

Episode Content

01:01 Overview of Separation Techniques in Dairy

04:51 Traditional vs. Modern Filtration Techniques

09:56 Benefits of Early Filtration in Cheese Production

10:31 Types of Membrane Filtration: RO, NF, UF, MF

12:32 Collaboration with Clients: Understanding Needs

13:54 Key Metrics Clients Look for in Filtration

21:11 Medium-Sized Dairy Innovations in Separation Techniques

24:47 Future Trends: Plant-Based and Hybrid Dairy Products

32:26 Closing Thoughts on the Future of Dairy Industry

Production

This podcast is brought to you by Au2mate.This podcast is produced by Montanus.

Curious about the latest technologies in Food & Beverage processing?In The Food Tech Podcast, we give you the latest trends, technologies, and automation knowledge that will accellerate your production process.See you on the inside.