LiDAR in food and beverage — flour, malt, sugar, cocoaLiDAR in food and beverage — flour, malt, sugar, cocoaLiDAR in food and beverage — flour, malt, sugar, cocoa

Food and beverage is a quiet market for industrial LiDAR. Breweries, flour mills, sugar refineries and cocoa processors have the same question as a cement plant — how much material is in the silo, in real time? — but they operate under a regulatory regime a cement plant will never see: hygiene compliance.

What sets food silos apart from industrial silos. Three points that turn every hardware spec on its head.

• Material contact. Anything that could potentially come into contact with food — including sensors — must be FDA- or EU 1935/2004-compliant. That includes the optical window of a LiDAR sensor if it is mounted where bulk material can splash onto it.
• Cleaning cycles. CIP/SIP, high-pressure water, and in breweries also hot-air sterilisation. An IP66 housing is often not enough — for food applications we typically spec IP69K with a 1.4404 (V4A) stainless-steel housing.
• Mostly low dust. Unlike cement or coal, dust load is usually moderate. But: flour dust is explosive (ATEX Zone 20 inside the silo), and powdered sugar likes to stick to polished surfaces.

The standard configuration. Across multiple anonymised brewery and flour-mill installations in Germany and Austria, a setup has settled in: OWL EYE® STOCKPILE or BUNKERS & FEEDERS (depending on vessel type) in a 1.4404 stainless housing with an integrated FDA-compliant optical window (typically Schott Borofloat® with food-grade gasketing). Power 24 V DC, data via OPC-UA into the existing MES.

Bulk density — the bigger uncertainty than the LiDAR measurement itself. Flour, malt and cocoa swing well beyond ±1 % by grain size, moisture and settling. That does not make the LiDAR volume measurement less accurate — it makes the volume → mass conversion the critical step. We therefore always ship a parameterised density table with food installations, fed from lab measurements or weighing data of the most recent delivery.

Material	Typical bulk density	Specific LiDAR notes
Flour Type 405	480–550 kg/m³	fine dust; air-purge optic cleaning recommended
Flour Type 1050	510–580 kg/m³	coarser, less dust carryover
Barley malt	540–620 kg/m³	easy to measure, very regular cone shape
Rye malt	600–680 kg/m³	darker — lower reflectivity, max range shrinks
Cocoa beans	580–700 kg/m³	reflectivity-stable, very easy to measure
Crystal sugar	800–900 kg/m³	reflective surfaces, watch direct sunlight
Powdered sugar	480–620 kg/m³	very sticky — schedule daily optic checks

How the data lands in production planning. Three use cases that show up in every food plant:

1. Batch traceability. If the flour silo level is continuously known, you can immediately document which delivery a batch came from. That simplifies EU 178/2002 documentation and accelerates a recall if it happens — hours instead of days.

2. Minimum-level alarm. A South-German brewery runs two brews per day per line — an empty malt silo at 2 am is a production stop. The LiDAR inventory feeds a reorder logic that pushes a request to procurement before the critical residual is reached.

3. Inventory value on the books. Food raw materials are far higher in value per tonne than clinker or scrap (cocoa can run €8,000–10,000/t depending on the market). An inaccurate manual inventory shifts the balance-sheet value of a mid-size plant by a six-figure amount per quarter — continuous inventory data is not just a comfort feature here.

What we do not promise in a food plant. LiDAR is not a trade-approved measurement. For commercial weighing at goods-in, the bridge scale stays mandatory. LiDAR is the continuous inventory measurement in between — accurate enough for procurement, production planning and the balance sheet, but not for the invoice to the supplier.

One recommendation. If you are planning an MES or ERP rollout anyway, scope LiDAR inventory in the same tender. The integration is significantly cheaper when the data lines are pulled once.

More on volume measurement for grain and agriculture at /getreide/, plus /bunkers-feeders/, /stockpile/ and /industries/.

Food and beverage is a quiet market for industrial LiDAR. Breweries, flour mills, sugar refineries and cocoa processors have the same question as a cement plant — how much material is in the silo, in real time? — but they operate under a regulatory regime a cement plant will never see: hygiene compliance.

What sets food silos apart from industrial silos. Three points that turn every hardware spec on its head.

• Material contact. Anything that could potentially come into contact with food — including sensors — must be FDA- or EU 1935/2004-compliant. That includes the optical window of a LiDAR sensor if it is mounted where bulk material can splash onto it.
• Cleaning cycles. CIP/SIP, high-pressure water, and in breweries also hot-air sterilisation. An IP66 housing is often not enough — for food applications we typically spec IP69K with a 1.4404 (V4A) stainless-steel housing.
• Mostly low dust. Unlike cement or coal, dust load is usually moderate. But: flour dust is explosive (ATEX Zone 20 inside the silo), and powdered sugar likes to stick to polished surfaces.

The standard configuration. Across multiple anonymised brewery and flour-mill installations in Germany and Austria, a setup has settled in: OWL EYE® STOCKPILE or BUNKERS & FEEDERS (depending on vessel type) in a 1.4404 stainless housing with an integrated FDA-compliant optical window (typically Schott Borofloat® with food-grade gasketing). Power 24 V DC, data via OPC-UA into the existing MES.

Bulk density — the bigger uncertainty than the LiDAR measurement itself. Flour, malt and cocoa swing well beyond ±1 % by grain size, moisture and settling. That does not make the LiDAR volume measurement less accurate — it makes the volume → mass conversion the critical step. We therefore always ship a parameterised density table with food installations, fed from lab measurements or weighing data of the most recent delivery.

Material	Typical bulk density	Specific LiDAR notes
Flour Type 405	480–550 kg/m³	fine dust; air-purge optic cleaning recommended
Flour Type 1050	510–580 kg/m³	coarser, less dust carryover
Barley malt	540–620 kg/m³	easy to measure, very regular cone shape
Rye malt	600–680 kg/m³	darker — lower reflectivity, max range shrinks
Cocoa beans	580–700 kg/m³	reflectivity-stable, very easy to measure
Crystal sugar	800–900 kg/m³	reflective surfaces, watch direct sunlight
Powdered sugar	480–620 kg/m³	very sticky — schedule daily optic checks

How the data lands in production planning. Three use cases that show up in every food plant:

1. Batch traceability. If the flour silo level is continuously known, you can immediately document which delivery a batch came from. That simplifies EU 178/2002 documentation and accelerates a recall if it happens — hours instead of days.

2. Minimum-level alarm. A South-German brewery runs two brews per day per line — an empty malt silo at 2 am is a production stop. The LiDAR inventory feeds a reorder logic that pushes a request to procurement before the critical residual is reached.

3. Inventory value on the books. Food raw materials are far higher in value per tonne than clinker or scrap (cocoa can run €8,000–10,000/t depending on the market). An inaccurate manual inventory shifts the balance-sheet value of a mid-size plant by a six-figure amount per quarter — continuous inventory data is not just a comfort feature here.

What we do not promise in a food plant. LiDAR is not a trade-approved measurement. For commercial weighing at goods-in, the bridge scale stays mandatory. LiDAR is the continuous inventory measurement in between — accurate enough for procurement, production planning and the balance sheet, but not for the invoice to the supplier.

One recommendation. If you are planning an MES or ERP rollout anyway, scope LiDAR inventory in the same tender. The integration is significantly cheaper when the data lines are pulled once.

More on volume measurement for grain and agriculture at /getreide/, plus /bunkers-feeders/, /stockpile/ and /industries/.

Food and beverage is a quiet market for industrial LiDAR. Breweries, flour mills, sugar refineries and cocoa processors have the same question as a cement plant — how much material is in the silo, in real time? — but they operate under a regulatory regime a cement plant will never see: hygiene compliance.

What sets food silos apart from industrial silos. Three points that turn every hardware spec on its head.

• Material contact. Anything that could potentially come into contact with food — including sensors — must be FDA- or EU 1935/2004-compliant. That includes the optical window of a LiDAR sensor if it is mounted where bulk material can splash onto it.
• Cleaning cycles. CIP/SIP, high-pressure water, and in breweries also hot-air sterilisation. An IP66 housing is often not enough — for food applications we typically spec IP69K with a 1.4404 (V4A) stainless-steel housing.
• Mostly low dust. Unlike cement or coal, dust load is usually moderate. But: flour dust is explosive (ATEX Zone 20 inside the silo), and powdered sugar likes to stick to polished surfaces.

The standard configuration. Across multiple anonymised brewery and flour-mill installations in Germany and Austria, a setup has settled in: OWL EYE® STOCKPILE or BUNKERS & FEEDERS (depending on vessel type) in a 1.4404 stainless housing with an integrated FDA-compliant optical window (typically Schott Borofloat® with food-grade gasketing). Power 24 V DC, data via OPC-UA into the existing MES.

Bulk density — the bigger uncertainty than the LiDAR measurement itself. Flour, malt and cocoa swing well beyond ±1 % by grain size, moisture and settling. That does not make the LiDAR volume measurement less accurate — it makes the volume → mass conversion the critical step. We therefore always ship a parameterised density table with food installations, fed from lab measurements or weighing data of the most recent delivery.

Material	Typical bulk density	Specific LiDAR notes
Flour Type 405	480–550 kg/m³	fine dust; air-purge optic cleaning recommended
Flour Type 1050	510–580 kg/m³	coarser, less dust carryover
Barley malt	540–620 kg/m³	easy to measure, very regular cone shape
Rye malt	600–680 kg/m³	darker — lower reflectivity, max range shrinks
Cocoa beans	580–700 kg/m³	reflectivity-stable, very easy to measure
Crystal sugar	800–900 kg/m³	reflective surfaces, watch direct sunlight
Powdered sugar	480–620 kg/m³	very sticky — schedule daily optic checks

How the data lands in production planning. Three use cases that show up in every food plant:

1. Batch traceability. If the flour silo level is continuously known, you can immediately document which delivery a batch came from. That simplifies EU 178/2002 documentation and accelerates a recall if it happens — hours instead of days.

2. Minimum-level alarm. A South-German brewery runs two brews per day per line — an empty malt silo at 2 am is a production stop. The LiDAR inventory feeds a reorder logic that pushes a request to procurement before the critical residual is reached.

3. Inventory value on the books. Food raw materials are far higher in value per tonne than clinker or scrap (cocoa can run €8,000–10,000/t depending on the market). An inaccurate manual inventory shifts the balance-sheet value of a mid-size plant by a six-figure amount per quarter — continuous inventory data is not just a comfort feature here.

What we do not promise in a food plant. LiDAR is not a trade-approved measurement. For commercial weighing at goods-in, the bridge scale stays mandatory. LiDAR is the continuous inventory measurement in between — accurate enough for procurement, production planning and the balance sheet, but not for the invoice to the supplier.

One recommendation. If you are planning an MES or ERP rollout anyway, scope LiDAR inventory in the same tender. The integration is significantly cheaper when the data lines are pulled once.

More on volume measurement for grain and agriculture at /getreide/, plus /bunkers-feeders/, /stockpile/ and /industries/.