I apologize if I used "data patterns" incorrectly. Here's some background. I'm porting an Access database to a web based MYSQL app. Here's what we are tracking.
We've got a machines with up to 16 heads. Each head has three items associated with it two are integers, one is a short text string. Each production order uses at least one head. Some use all 16, some use only one. If more than one head are used, we track the order they are used in. Each production order has a few short to medium length fields in addition that are stored as well. The vast majority of production runs use less than half of the given heads.
Currently the data is in an Access database that stores everything in one table, so there are 6 + (16*3) 48 fields stored per row for a total of 54 columns. The only fields that are searched in are second two, which are integers.
id|workorder|partnumber|note|machine|reference|head1spec1|head1spec2|head1spec3|head2spec1|head2spec2|head2spec3|
...etc to head 16
I aware that there is a lot of dead space in there, since each row contains 16 elements that could be broken into a separate table and joined to display results. It's been acquiring data for about 10 years, right now the file size of the Access DB is 60.8 MB
Here's my question. Is there any real world advantage to normalizing (maybe not correct usage) in this case since none of that data is used for searching, and having it all in one column is sort of a natural state for that information?