RESNA 27th International Annual Confence

Technology & Disability: Research, Design, Practice & Policy

June 18 to June 22, 2004
Orlando, Florida

Design of an Assistive Bulk Packaging Tool

Matt Bohm, Todd Sparks,
Yogesh Thakar, Nagesh Mula
University of Missouri - Rolla


This paper describes the transformation of an imprecise counting and packaging line at the Rolla Area Sheltered Workshop into an accurate placement type assembly line to assist disabled workers. The device prototyped at University of Missouri – Rolla (UMR) was the product of several modern design methodologies. Initial customer interviews were conducted, a customer needs questionnaire developed, technical requirements were formed and several types of concept generation techniques were applied to this original design project. The end result is a highly useful and simple device that has greatly improved the accuracy of this process.


Bulk Packaging, Assistive Device, Counting


The Rolla Area Sheltered Workshop employs persons with mental and physical disabilities to package variety boxes of dog and cat food sample packets for Royal Canin, a local pet food manufacturer. The current method of packaging involves individuals removing product from large bins and counting the product as it is placed into smaller boxes. The boxes are then handed off to another individual for a different type of product to be added. Royal Canin does not mind if the sample boxes are off by a few individual packets, however, the current accuracy of packaging does not always allow for this small deviation. Previously, the only method of checking the boxes, short of recounting, was to weigh the packed boxes. Weighing the packaged boxes is not accurate either due to the variation of the weight of the individual sample packets. In the interest of increased productivity and a reduced incidence of repacking, a counting and packaging assistive device was sought.


The design team began by meeting with the Rolla Area Sheltered Workshop and observing the previous method of packaging used by the employees. At this point the Workshop did not have any specific solution sets in mind, only that they needed to increase packet count accuracy. An informal two-way question & answer session took place between the design team and Workshop managers so that both groups had an understanding of the problem and what types of design solutions would be valid. From the initial Workshop meeting a formal customer needs questionnaire was developed. The questionnaire, given to Workshop managers and assistants, gathered and ranked specific needs information about the desired product on a 1 to 5 scale.

After compiling the results of the questionnaire the highest ranking needs were found to be: safe operation, repeatable product count, team operation and comfortable operation. Team operation is important to the Workshop because it allows for persons with different abilities to work together and complete the desired task. Even after a thorough customer needs analysis, no specific form or set direction was established for the product. An ethnographic study was then conducted, making use of pictures taken first hand by workshop employees and video taken by the design team and workshop managers. The video and photos were reviewed heavily and a functional model of the desired product was created. A functional model is block diagram representation of an object describing functionality with a defined basis. By making use of a functional model, “what?” the product needs to do is determined while leaving “how?” the product works to creativity and ingenuity.

With the product's functional model in the design team toolbox, several concept generation methods were followed that in all counted for 31 different concept variants. The concept variants came from the Morphological Matrix, C-Sketch, Design by Analogy and Chi Matrix techniques (1). The Morphological Matrix approach involves sketching out multiple solutions for individual functions in matrix grids. Individual solutions are then aggregated to form the overall concept. The C-Sketch method involves each design team member drawing an individual solution and then passing each sketch on to another team member. As the sketches are passed around, each team member augments the drawings. This procedure is repeated until every team member has had input on every design variant. The Design by Analogy and Chi Matrix techniques both involve relating the current product to past design knowledge and artifacts to generate concept variants.

Figure 1. Chi-5 Concept Variant

A set of qualitative metrics were applied to reduce the 31 concept variants down to five distinct concepts. With the set of five concepts a quantitative evaluation was then performed. The quantitative measures used were: Cost, Flexibility, Production Rate, Steps to Operate, User Feedback and Manufacturing Lead Time. A rudimentary bill of materials for each concept based upon the geometric sketches and electronic features was created for each concept and used to determine a good estimate of concept cost. Since the current production sets (type and number of sample packets in a box) may change, flexibility was measured using the cost of any components necessary to modify the concept to work for different production runs. Production rate was estimated based upon simple experiments to determine how long the actions used in each concept would take. The number of steps to operate were also determined by simple experiments, a simple device would require few motions to operate while a complex device would require many. There are two distinct types of feedback 1.) an audio or visual electronic signal and 2.) a continuous tactile visual feedback. Both types of feedback were aggregated into a single feedback rating by normalizing and performing a root mean square calculation on each feedback type. Because time was a factor during this design project, manufacturing lead-time was calculated, in days, for each concept.

Figure 2. Proof of Concept Collage

In order to combine the disparate rating criteria into a single overall concept ranking, the design criteria were ordered by importance. Tradeoffs were then evaluated between the individual criteria. For example, at what point is cost too great for an increase in flexibility, at this point the two criteria are said to be equal. Applying this methodology, a mathematical system can be created using all of the design criteria. From the solution of the system of generated equations, a single numerical rating can be assigned to each concept. The concept labeled Chi-5 (Figure 1), had the highest overall rating and was the best design based upon the selection criteria.

Figure 3. Alpha Prototype


As part of the design process a simple proof of concept was constructed to prove that a significant principle behind the chosen concept was valid design solution. Because of the simplicity of design and minimal material and construction time required, additional proof of concept variants were built (Figure 2), drawing elements from all five of the heavily scrutinized reduced set of concept variants. These variants along with the original proof of concept were demonstrated to the customer. Managers from the Workshop used and evaluated each concept. While the managers liked all of the concepts, a wish list containing discrete elements from the presented concepts was created for their desired product. One of the constructed concepts closely resembled the features and layout of the desired product and was dubbed as an Alpha Prototype (Figure 3).

Figure 4. Beta Prototype

The Beta Prototype or finished product (Figure 4), builds on lessons learned throughout the design and manufacturing stages as well as customer feedback during the design project. The final solution to the design problem replaces the counting operation with a pick and place operation. The product is designed to stand over a box and guide the worker on the placement of packages.


  1. Otto, K. and Wood, K. (2001), Product Design: Techniques in Reverse Engineering, Systematic Design, and New Product Development, New York, Prentice-Hall.
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