The solid wood industry is somewhat unique, due to the biological nature of the material being processed. Manufacturing processes impact many thousands of pieces every day, each piece with unique characteristics that challenge optimization scanning systems. An ongoing challenge that is not resolved by the optimization system may result in considerable lost value to the saw miller.
Bowed lumber is an ongoing challenge that will cause portions of the piece to lift off of Top of Chain and vibrate vertically with varying degrees of frequency. No two pieces of bowed lumber will be exactly the same, but10% of a day’s pieces may exhibit signs of the bow. The next day’s product mix may exhibit less bow, substituting instead another characteristic, perhaps related more to the steep edge wane of a smaller average diameter log. Ends may exhibit stepped, beveled or broken fiber direct from the forest or as a result of the sawmill manufacturing process. Other manufacturing imperfections may include snipe along the length in width or thickness.
Edges or faces may be untouched or partially touched by the manufacturing process, resulting in ‘live’ faces or partially ‘live’ faces of varying thickness’ and straightness on the edge. Arun of ‘reman’ from the yard may have weathered long enough to exhibit a greater degree of warp, creating misloading of the piece prior to the scan, ‘rocking’ of the piece through the scan, and wide faces that are not parallel to the Top of Chain.
Lumber characteristics may also be combined in any combination. These characteristics and more, in varying degrees of deviation from negligible effect to the extreme, create the demand for accurate profile sensing that will not falter when called upon.
Lumber mills also have demanded ever better width, and length accuracy’s in addition to the softwood mills’ gravitation to faster line speeds.
This propensity for unique lumber characteristics and combinations of lumber characteristics combine with mill production expectations to require a sensor designed specifically for lumber (solid wood products). The challenge for optimization vendors who intend to be in the wood products business for the long haul is to provide lumber scanning that extracts consistently accurate profile measurements to feed the optimization ‘engine’ for a wide variety of lumber characteristics and solid wood product market applications. It also is erroneous to presume that lumber presentation and characteristics are restrained to limits experienced in another industry. For example, a sensor designed to measure materials with relatively homogeneous characteristics such as metal plates or ingots or panels may not produce the required results in the solid wood industry. And the optimization engine scores each piece of lumber based on what the scanner ‘sees.’ At the end of the day, system performance begins to depend on luck when a profile sensor feeding measurements into the system fail to recognize certain lumber characteristics correctly.
Optimization vendors with limited experience and/or sensing expectations in the solid wood industry might offer consumers a sensor for reasons other than the quality of sensing. Sensor selection might be due to simple availability (for example, what is available from the scanning supplier’s shelf), or some historical offering of their own design, or cost. In order to promote their system, optimization vendors that utilize sensors with a tendency to mis-measure certain characteristics of lumber profile may rely on other sensing arguments (for example, profile density, price, wood quality input, seemingly generic studies). These other arguments are certainly viable considerations for the saw miller, as long as they ‘sit’ on top of consistent and dependable lumber profile measurements. The consumer, of course, is the final discerning factor, determining which optimization system works best for their application.