Champion saves the day: Volume 2 Production

In-process and at-line NIR for production

Beat the costs in production! Download Volume 2 of the Champions’ Guidebook and find out how to save money while monitoring production lines.

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Our determined (and love-struck) food champion, Max, is back at it. Check out the newest animated video to see how NIR can avoid costly production errors (and increase profitability) after googly-eyed Max’s big goof-up.

One of the greatest assets of on-line and at-line NIR is having a second set of (focused) “eyes” on production operations. The NIR can be trained to measure critical material properties for in-process or finished products, or even do simple identification procedures to confirm questions like: is Product A is actually being produced?

Max may be a little distracted at times, but NIR can still make him a champion!

Be a Food Analysis Champion!

Save time with efficient incoming goods inspection

New BUCHI campaign delivers 3 e-booklets to create Food Analysis Champions!

beattheclock

Every day, food producers undergo myriad processes and procedures designed to achieve a quality product and (hopefully) a profitable business.

The loading docks and warehouse serve as initial points of contact for ingredients and foodstuffs that will become integrated into delicious (and sometimes nutritious) food products. It is the obligation of the producer to ensure that they are obtaining the highest quality and correctly priced goods prior to feeding those ingredients into the production process.

Our first booklet provides insight into challenges and opportunities related to incoming goods inspection, including:

  • Typical slow-downs in incoming goods receiving
  • Tips to meeting incoming goods inspection requirements efficiently
  • Benefits of using fast, non-destructive NIR analysis for testing incoming goods
  • Improving time-to-result for classical reference methods (i.e. extraction and Kjeldahl)
  • Sample NIR and classical testing applications to help you save time!

Download this complimentary resource, and stay tuned for future additions to the series, including: production and finished goods control!

For some nice (and enlightening) lunch break entertainment, watch our Food Analysis Champion, Max, save the day when production is halted due to QC backlog in the BUCHI animated video short series for “Beat the Clock.”

 

BUCHI NIR is Pro-Food Quality at ProFood Tech

The BUCHI wagon got put back on the road for the ProFood Tech conference in Chicago this week. Hopefully you’ll catch us at our booth at Lakeside Upper Hall #3113 (vs. catching our booth attendants just lurking the show floor devouring free samples all day).

ProFood Tech is an event, and BUCHI is a laboratory equipment manufacturer, but you might be interested in the overlap between us. We serve many of the same industries. NIRSolutions_bread

Baking and Snack

We already blogged about some of the sweet stuff BUCHI can do in the chocolate industry, but we offer analytical measurements for many raw materials used by the baking and snack industries:

  • Whole & ground cereals (e.g. wheat, semolina, barley, rice, corn/maize)
  • Hulls & bran
  • Oil seed meals
  • Fats & oils (e.g. vegetable oils and animal fats)
  • Egg &  milk derivatives (e.g. egg powder, liquid egg, milk powder)
  • Dry pasta & noodles
  • Ready-meals (e.g. lasagna, frozen pizza)
  • Confectionary (e.g. chocolate, cocoa & derivatives)

Meat, Poultry and Seafood

Protein builds muscle, and BUCHI has flexed some muscles in the QC of many meats and meat products, including:

  • Animal meat (e.g. beef, pork, turkey, wild animals)
  • Fish meat
  • Sausage
  • Animal flour
  • Fish meal
  • Pig adipose tissue

Dairy

If I could survive on cheese and ice cream alone, I would. Our BUCHI NIR products are used to make sure that the stuff that goes into milk and milk products are in-spec. We can help you analyze important sample properties for things like:

  • Milk
  • Yogurt and fresh cheese
  • Hard, semi-hard and soft cheese
  • Processed cheese
  • Butter
  • Milk creams
  • Milk powders

Frozen and Prepared Foods

When you don’t have time to cook or time for long laboratory analysis methods.  BUCHI NIR has methods developed for:

  • Dry pasta/noodles
  • Ready-meals (e.g. lasagna, meat pie, meat & fish ready noodles, frozen pizza)

Beverage

Drink up! BUCHI NIR can be used for quality control of beverages:

  • Distillers grains
  • Milk powders
  • Chocolate (e.g. cocoa & derivatives)

Getting hungry for more information?

Check out our Application Finder on the website or Contact us to talk about your specific application needs.

Chocolate. The quality side.

QC of cocoa & chocolate using NIR

Last week the BUCHI Group gathered in the mountains of Pennsylvania for our annual national meeting. Jerry Richardson, our Product Manager for BUCHI Kjeldahl, Dumas and Extraction, decided to lure the sales group in with a session modeled around a topic near and dear to so many – chocolate.

Chocolate

Being a Swiss company, you know we have had our hands in the chocolate industry. In fact, one of the largest Swiss chocolate makers has been using BUCHI NIR in their quality control program for years. (If you aren’t familiar with NIR yet, please start here!)

Quality

Just as is echoed across most of the food industry, cocoa and chocolate manufacturers rely on analytical methods to monitor and control quality parameters such as moisture, fat, protein and sugar content of their incoming, in-process and finished products. These critical quality parameters impact the taste, texture, shelf-life and cost of our beloved confections.

So, we circle back to the obvious question – how would NIR support the quality and profitability of a cocoa or chocolate manufacturer?

It starts with the bean

Cocoa beans of course are the most important ingredient in chocolate, but the imported bean quality will vary depending on the – sometimes dynamic – environmental conditions of the region where they were grown. Quantification of the fat content in the beans and intermediate products can help ensure consistency in final products. Another important quality parameter is moisture content, which can be used to monitor the roasting process.

The reference method for fat is the Weibull-Stoldt method, a traditional acid hydrolysis followed by Soxhlet extraction in ether; the reference method for moisture is Karl Fischer titration. Both methods require sample preparation, chemical reagents, skilled technicians and extended analysis time. In contrast, beans can be placed in a sample cup on the NIR and both fat and moisture can be measured simultaneously in as little as 30 seconds. The non-destructive, rapid NIR method can be used to make decisions regarding cocoa bean processing – for example, whether or not roasting is complete.

While it’s easy to think of the NIR as a magical black-box, these measurements are based on the interaction of light with your sample. The carbon-hydrogen and hydrogen-oxygen functional groups representative of the sample fat and water content, respectively, are readily measured using NIR spectroscopy. Applying a calibration model, we can quickly relate the sample spectra back to its composition (e.g. fat and moisture). Of course, the calibration model is based on samples of known composition, and the primary reference methods (Weibull-Stoldt, Karl Fischer) need to be employed to generate and validate the relationship between spectra and the quality parameter of interest.

Cocoa Mass, Cocoa Butter and Cocoa Powder

The theme of quick, non-destructive measurements doesn’t end with the bean. NIR has also been applied to measure moisture and fat in nibs and cocoa mass, free fatty acids and iodine value in cocoa butter, and moisture and fat in cocoa powder. These measurements can be used to maximize the cocoa butter yield from the cocoa liquor, ensure the standard of identity specifications are met without excess addition of expensive ingredients like cocoa butter, and to determine the fat content on which the products should be sold; these applications could have a significant impact on production efficiency and profitability.

Confectionery products

Calibration models using NIR have also been developed for key confectionery product categories, including: milk and dark chocolate. Parameters include: moisture, fat (including solid fat at room temperature), lactose, sucrose and theobromine.

As it turns out, the session’s brainchild, Jerry, was himself a closet chocolatier. He built his own chocolate lab in his home. I have yet to quality-check his product portfolio, though I’ve heard good reviews. After hearing him talk about chocolate, I can at least vouch for his devotion to his craft.

Additional information

For additional information, take a look at the BUCHI Application Finder to see what we have published in way of chocolate analysis. You’ll find applications using extraction and hydrolysis, speed extraction, Kjeldahl and NIR. Please note that not all applications are published; if you have an application in mind, consult a BUCHI representative to see if we have experience within our local or global network!

 

Feed Manufacturing: Profit with In-line NIR Process Control

The BUCHI Crew is hitting the road this week for the 2017 International Production & Processing Expo (IPPE) in Atlanta, Georgia. Sounds peachy! Find us in Hall C, Booth 205.

IPPE is hailed as the largest annual trade show for the poultry, meat and feed industries. The show focuses on innovation, education, global reach and networking. So, what does BUCHI have to offer these industries? Let’s talk about real-time process monitoring and how it plays into profitability. 

Is moisture content in feed synonymous with profit margin? Talk to a feed producer and you’re likely to see a head nodding in agreement.

How valuable would it be to have a continuous read-out of the moisture content of your feed at points along the process where you can still adjust your process to reach a moisture target? Sounds like money in the bank, and BUCHI near-infrared (NIR) spectroscopy is a proven tool for the job. It’s also possible to monitor other critical feed parameters, like protein and fat, simultaneously.

Check out this short note showing how a BUCHI NIR-Online® process analyzer was used to monitor fat, protein, moisture and crude fiber after the mixing step in a feed operation. Or, read below for a case study at the German RKW mill that produces 75,000K tons of mixed feed annually and uses BUCHI IR-Online® to improve profitability.

The production process

At the RKW Kehl production facility the process begins with a check of raw materials for upcoming orders. The feed is predominately composed of soy and maize cereals, with minerals, vitamins and amino-acid supplementation. Feed composition is obtained by the required moisture, fat, protein, crude fiber and starch of each recipe. Due to the inherent variability of these nutrients in the incoming raw materials, the ratio of raw components needed to fulfill the nutrient profile of each recipe must be recalculated daily.

Mixtures under scrutiny

Raw materials are selected, scaled and mixed according to ordered batch recipes using the process control system. The quality control group determines whether a feed mixture falls below a required protein or fat content, or if moisture needs adjusted to meet specifications. Prior to the installation of the NIR-Online® process analyzers, the answers to these questions came from traditional laboratory analysis with long wait times. Now, the answers are streaming in real-time using the NIR-Online® device at the end of the mixing unit.

Near-infrared (NIR) light emitted from the sensors illuminates product through an installed window resulting in absorption by the sample, which is characteristic of its composition.  These readings are visualized in process charts by personnel in the switch room. If preset parameters are over- or under-run, corrective adjustments can be made immediately. Integration of the NIR-Online® products with the existing process control system provides the opportunity for automatically generated, highly detailed process documentation.

In-line control

“[Because the process can be stopped or adjusted early in production if specifications are not met] the utilization of NIR-Online® has minimized expensive rejects and complaints,” said Mr. Lühr, as he described the financial advantages of the NIR-Online® solution. “This benefit is further increased with the possibility of adjusting moisture content in real time.”

The NIR-Online® process software calculates the difference between the in-line property measurement and the batch set point without stopping production, ensuring moisture addition is precisely controlled for each batch.

“If we are able to converge within 0.5% of the moisture set point of a batch, we can sell more than 375 tons of additional mixed feed per year – a substantial benefit. “The investment in NIR-Online® technology will be paid for in a few months”, Mr. Lühr stated.

Find out more

Use the BUCHI Application Finder to explore additional application notes related to NIR in the feed industry. Or, Contact Us to get details on the broad array of feed materials and properties that can be measured by NIR.

Looking for a different technology? Click here to see results that include applications for all of the BUCHI product solutions for the feed industry, including: Kjeldahl, Dumas, extraction and spray-drying.

 

Training an NIR?

Sample planning & calibration

Buy a whistle and some orange cones and lace up your high-tech sneakers. Time to break a sweat.

NIR spectroscopy is a secondary technique. That means that the analyzer isn’t directly measuring water content in pet food kibble or fat in cream cheese. But with a good chemometric software package  and some quality reference lab data, you can train it better than a Best in Show German Shepard at Westminster.

BUCHI has already done some heavy-lifting, developing calibrations for key quality parameters across various industries. Check out the BUCHI Application Finder to see if we have a Plug & Play solution already developed for you!

Let’s say you want your at-line NIR to measure protein in dry kibble. First, you make a plan to gather samples from several production batches or across a number of kibble product skews so that the samples you’ve collected have a decent range in protein (and other variables that NIR is sensitive to, like moisture, fat and ash). The rule of thumb for the target range is about 20x the standard error of your reference lab technique. Pour kibble into a sample container, collect the NIR spectra, then send each sample off for analysis by Kjeldahl. Once the Kjeldahl protein measurements come back, you plug that information into your NIR software. Now, each spectrum has a reference property of protein associated with it. The next step is to build a calibration model. It’s the mathematical equation that relates your multivariate X-data (spectra) with univariate Y-data (protein). Luckily for you, the software does all of the heavy lifting, typically using partial least-squares regression, and spits out a calibration equation that you can then use to measure the protein content in future production samples. Splendid.

When  you’re looking to do qualitative testing, like 100% inspection of all of your incoming raw materials, the idea is the more or less the same: sample plan, collect NIR data, collect primary data, assign properties, create calibration model using chemometric software. The sampling plan should include a note to gather multiple lots of every raw material (rule of thumb: 5 lots or more). You want to use those lots to train your NIR to “see” and be desensitized to all of the acceptable and expected sources of variation, like vendor, particle size, or moisture content. Once you’ve collected NIR spectra for each lot, ship the samples off to some legit lab that can validate their identity and quality. If the samples pass the test, go back in the software and assign a chemical identity as a property for each spectrum (e.g., “sucrose” or “alanine”).  Then, sit back as your chemometric software does something fancy like Soft Independent Modeling of Class Analogy (SIMCA) so that you can use your NIR to test the identity of future incoming samples. This type of analysis also works to establish blend uniformity or finished product conformity. Way quicker than HPLC.

What if the calibration performance takes a hit?

Things could roll along pretty smoothly for awhile and you’ve cut way back on the number of kibble samples you’ve been checking by Kjeldahl for protein. Then something changes; a new sources of variation has entered the fold. Maybe your kibble got an extra boost of fiber in the formulation to keep the terriers regular. Or maybe some new dryer equipment is reducing the moisture content of your kibble lower than when you developed the first calibration model. All of a sudden, your NIR measurements aren’t as accurate as they used to be. Or maybe the analyzer software is spitting out measurements, but they are marked with red flags.

The fact is, formulations evolve, plant equipment ages or is replaced, a record humidity summer sets in. Things change, and when they do, it’s time for a calibration update.

The effort in a calibration update is essentially proportional to the magnitude of change affecting the sample/product/process. If there is a new kibble skew that has slightly higher fiber, add 10-20 sample spectra with Kjehldal reference data to the calibration set, recalculate the model and test the updated model with some new lots. If it works, meaning you’re getting an acceptable standard error of prediction, you’re back off to the races.

If you’re a current BUCHI customer needing support in calibration development or calibration update, contact us!

If this post was enough to wet your whistle, be sure to click the [FOLLOW] button on your browser to get access notifications of future content where we will delve deeper into the details of calibration development, performance and maintenance.