Taking a new product from the lab to the plant floor and out the door to the consumer is a daunting process for most product developers. Some companies are so fearful of changes in product quality during scale-up that they insist on conducting consumer tests only on products made on manufacturing systems at production scale.

This drives consumer testing to the back end of the product development sequence and forces sometimes inaccurate assumptions to be made about consumer needs. Mishandling scale-up can not only raise product development costs, it can delay launch and ultimately deliver a product that falls short of consumer expectations.

But what exactly is scale-up? And how can food companies ensure success?

Scale-up, in the context of this article, is not only the changes that can result from increasing equipment size. Considered broadly, scale-up is the collection of changes that occur between the laboratory prototype and full-scale manufacturing. These changes may include:

• Formulas, processes or packages to fit manufacturing capabilities or economic constraints.
  
• Ingredient sources or manufacturing locations.
  
• Ingredient target levels or a wider range of ingredient levels than was tested in the lab.
  
• Batch vs. continuous process.
  
• Larger or smaller vessels.
  
• Faster or slower movement of product.
  
• Longer or shorter "cycle times" for the product depending on the specifics of the lab process vs. the plant process.
  
• Ambient conditions.
  
• Manual vs. automatic packaging systems.

While the consequences of such processing modifications are numerous, they are by no means out of a manufacturer's control. In fact, by following certain guidelines, companies can predictably manage the effects of these changes between lab and plant scale. Drawing on more than 40 years of combined experience in product development and engineering, contributing editors Leslie Skarra and Bob Porter offer the following guidelines to help prevent a new product launch from becoming a new product failure.

Articulate Assumptions

New product development team members frequently implement assumptions that they do not articulate. For example:

• Marketing may assume that the product delivered from the final manufacturing plant will be an exact match to the product in the volumetric consumer tests early in the development process. Discussions here could include a definition of "exact match" and possible testing to determine a broader range of products that deliver equally well to the consumer proposition.
  
• Manufacturing may assume the new product will use current bulk ingredients. However, if the company has multiple manufacturing sites, each with different sources of raw ingredients, then either the product must be tolerant to those differences or the specific manufacturing line needs to be identified early in development.
  
• Assumptions made about economics may later require cost reductions in the formula or package. Experienced team members can anticipate the areas where costs creep up and set realistic cost parameters early in the project.
  
• Engineering testing is often executed on materials or processes that are "close" to the final situation, but not identical. Each difference should be noted and testing performed, if possible, to determine how the simulation differs from the final product or process.
  
• Timetables are full of assumptions. Team members should complete ruthless discussions of critical dates and back-up plans early in a project.

Identify Consumer Critical Range

There are two approaches to testing consumer proposition.

1. A single product is tested, is a hit with consumers and becomes the "gold standard" for scale-up. We call this the "pinnacle of product quality" method.

2. A range of products is identified that deliver to consumer needs. The effects of differences in attributes, like cost, size, color and package features, are understood, and acceptable ranges and trade-offs are defined. This is the "highest plateau" method.

Development costs for a project with a single gold standard target are two to four times higher than for a similar project with a product range defined as the target. The increased costs in development are driven by the need to match the target. In the product range approach, however, minor deviations can be accepted if they do not occur on critical attributes.

The matching process can drive issues as products are scaled up from the bench to plant scale. The greater up-front consumer testing costs and time to define acceptable consumer ranges are more than paid back during the scale-up and start-up stages.

Create a Robust Product Design

Very simply, robust product design results in products that are impervious to variation in key ingredients or process parameters. Given information on consumer sensitivities, the developer can then determine changes that trigger differences in important consumer attributes.

Initial bench-scale processes often focus on the easiest way to generate a range of prototypes for consumer assessment. As a prototype becomes more interesting, start processing that prototype in the lab as closely to plant processes as possible. Unit operations and time frames between processing steps should be simulated at small scale. Changes in lab processing that result in important changes in product quality are an indication of possible scale-up problems.

Once you have identified potential unit operations, review the relevant scale-up equations. You can find these in the literature, from your corporate process engineering department or from university food science/chemical engineering departments. Each unit operation will have a series of equations that explain how size of vessel, speed of movement, energy input, etc. will affect measurable quality parameters such as temperature, viscosity and elasticity. Use these equations to specify pieces of equipment or to design tests that will determine a product's sensitivity to key changes.

At this stage in development, you should have a detailed understanding of the controlling factors for product quality. Armed with the equations, ingredient information and prior test results, you should be able to reproduce results at will. You should also be gradually able to predict the effects of changes in ingredients, process equipment or scale in advance.

Test at Pilot and Full Scale

Subtle differences in test conditions can cause major differences in test results. The following three areas are some of the most troublesome.

Age, time and condition of materials used. When testing unit operations such as conveying, it is often not possible to mix fresh batches of material at the test location. Thus, materials are mixed or otherwise processed in advance and used for testing. Sometimes this approach is effective, but often, subtle differences in materials occur over time.

For example, with many products, moisture from one ingredient may transfer throughout the batch over time, resulting in changes in flow characteristics from fresh to aged. If the only way to test equipment is with aged material, it is useful to identify possible changes that could occur in fresh vs. aged materials.

As larger batches are mixed, the rate of movement of product into the process may actually slow down rather than speed up. Thus, material may be older when processed in the scaled-up system than it was in the lab system.

Recycle of scrap is commonly built into project economics, but its inclusion into processed product can impact product quality and is often overlooked until late in scale-up. For certain products, this can cause major changes in flow properties and finished product quality.

Speed. Scale-up testing is best when performed at plant speeds, even if only for brief periods of time. Many effects on product quality and manufacturability are due to line speed. Bigger equipment may not always be the best choice. Sometimes, "smaller and more often" may be the better direction for scale-up.

Product piece weight control, depositing accuracy and variability, and assembly (folding, cutting, shape retention) seldom improve at higher speeds. Speed also negatively impacts product transfers and positioning, maintenance of lanes and alignment, and traying. Conveyor belts may perform differently at manufacturing speeds due to differences in vibration or air flow with plastic vs. metal, belt configurations, etc. Air flow and product velocity significantly affect freezing conditions.

Packaging equipment becomes less tolerant of small variations in size and shape of products as speeds increase. Products will have to be held to more precise dimensions the faster the line runs.

Packaging equipment should provide a means to "catch up" from downtime. Unfortunately, this surge capacity is often cut out of the plan due to capital cost constraints.

Ambient conditions. Ambient conditions and seasonal changes affect the operating parameters of many unit operations. Murphy's Law dictates too often that experimentation will be done in one season and scale-up in the opposite season.

The availability of make-up air to permit combustion systems to function properly affects bake conditions. In warmer months, make-up air may be available, but in colder months, the plant may be closed and special provisions may be necessary to supply make-up air to control bake conditions.

Moist ambient conditions also affect cooler/freezer performance. The incursion of moist air from adjacent processes or changed weather conditions will affect efficiency and reduce time between defrost cycles. Condensate on product surfaces will significantly affect handling characteristics.

Ambient conditions affect the flowability of ingredients and may affect batch times due to plugging and hang ups in the system. Condensation may also affect moisture content of the materials, in some cases enough to alter product functionality as well as flowability. Raw materials entering mixers may be of different humidity and temperatures and require adjustments in factors such as ice/water ratios and cryogenics.

Develop a Realistic Schedule

Experience demonstrates certain scale-up activities always take longer than expected. One good rule of thumb is to allow double the planned time for these activities, as they are particularly vulnerable to delays.

"Black box" equipment prototypes never seem to work on the first try. Even if they work reasonably well, additional iterations usually enhance performance significantly. Since these prototypes are completely new (hence, black box), they can be the most difficult to get right.

Allow extra time for full-speed prototypes for critical unit operations. Candidates for full-speed testing include those operations determined to be critical to product quality in earlier robustness testing, those that affect product appearance, and those that affect alignment if packaging dictates. Product and package integrity may be impacted by speed.

If possible, pretest major new pieces of equipment prior to release from the equipment vendor's facility. This allows time and expertise for rework if required. It seems that the more expensive the equipment, the more likely it will have issues.

Planning, communication and realistic expectations will ease scale-up issues. Bob Porter is senior project manager/ chemical engineer at Food Systems Design Inc. (www.foodsys.com ) in Bloomington, Minn. He has more than 25 years of process engineering experience gained from domestic and international assignments for major food companies. Bob can be reached at 952-884-4048 or brporter@foodsys.com.

Leslie Skarra is the owner of Merlin Development Inc., Plymouth, Minn. The contract food product development company specializes in new products in most application categories and solves tough technical problems while creating great-tasting products. Phone: 612-475-0224; E-mail: lskarra@merlindev.com.