Hello Jason.

You would have to implement stemming on your system - in information retrieval, this is a process that reduces words to a common root. You can think of a stemmer as a map from the real world vocabulary to a "root dictionary" (which would only include the "roots" or the concepts of each real word term). A stemmer usually reduces plurals (cats and cat maps to cat), verb tensions (am and was could map to be), and synonyms (advocate could map to lawyer).

For example, in your case, your stemmer could map e-beam and ebeam to the root beam. It could also map i-beam and ibeam to beam.

You can implement generic stemmers (there are some well-known algorithms for english text), or rule-based stemmers. But you will most likely have to tune your stemmer based on actual user queries and expected results.

Now what you would have to do is to store the stemmed terms in another database attribute (let's name it StemmedText). So if you have a record containing the text e-beam, in your StemmedText attribute it will store the text beam.
When the user searches with the text e-beam, you will have to stemm the query text (which will give you beam), and then use a LIKE on the StemmedText attribute. Note, however, that if the user enters the text i-beam, he/she will find results containing e-beam (because both words stemms to the same root).

Hope this helps.