Masters Theses

Paul C. Stumb

Date of Award

6-1987

Degree Type

Thesis

Degree Name

Master of Science

Major

Industrial Engineering

Major Professor

Elden L. DePorter

Committee Members

D. H. Hutchinson, J. C. Hungerford

Abstract

The technology of bar coding has been In existence for nearly forty (40) years but has only recently found much application in modern industry. This fact is attributable in part to the evolution of the bar coding symbology itself (of which there are at least 16 in use today), but to a larger extent to the technological advances that have greatly improved the ability to both print and read bar coded symbols. The text of this document examines a number of these technological advances and evaluates the contribution or impact of each to the usefulness/success of a bar code system.

While bordering on a taxonomy of bar coding, the first two chapters of the text are intended to provide an overview of a bar code system—its applications and components. The critical elements of any bar code system are defined as hardware, software and environmental/ human factors, and it is the complex interaction of these three elements on which the success of a bar code system is contingent.

Although several methods for measuring the success of a bar code system are certainly plausible, the most appropriate or revealing index of success is identified as First Read Rate (ERR), for a low ERR will virtually guarantee user rejection of the system in favor of a more traditional yet undoubtedly slower and less accurate method of data collection or reporting. But while the the importance of a high ERR is generally accepted, the factors or parameters that impact ERR are to a large extent still unknown.

As each of the three major bar code system components are examined, two categories of associated parameters are identified. These are:

1. GO/NOGO Parameters

2. Level of Success Parameters

Of the "level of success" parameters, the quality of the printed media or print technique is often purported to be the single most important criterion in determining FRR. Other potentially significant contributors to the success of a bar code system, however, include the bar code application (defined herein by label length), and the human variability of the operator(s) that must use the system.

Chapter III of this text outlines an experiment designed to characterize the impact of these three parameters on the FRR of a bar code system. In Chapter IV, a mixed-effects linear model is defined, and factorial analysis of variance (ANOVA) techniques are used to analyze the results of 4800 attempted "reads" which represent the FRR data for every possible combination of four (4) print techniques, three (3) application/label lengths, and two (2) randomly selected operators.

Contrary to the assertions of many "experts", the results of this experiment lead to the conclusion that the operator effect and the interaction effects between operator and the other experimental variables are likely to have the greatest impact on a system's FRR. This conclusion suggests that success of the overall system is tantamount to success in controlling the operator variability, and that more attention should be given to the definition of human factors such as operator training than to the specification of system hardware--as is so often the case.

The text of this document concludes with some recommendations for additional experimentation and research in this field, and finally with an assessment of future trends with respect to the technology of bar coding and in a broader sense the entire field of automatic identification.

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