Effect of Cutting Bill Requirements on Lumber Yield in a Rip-First Rough Mill

In recent years, producers of solid wood dimension parts have emphasized improvements in lumber yield, focusing primarily on lumber grade and cutting technology rather than cutting bill design. Yet, cutting bills have a significant impact on yield. Using rip-first rough mill simulation software, a data bank of red oak lumber samples, and a cutting bill that resembles those used in industry, we determined the effect of changes in part size within an existing cutting bill and the impact of part-quantity requirements on yield. The results indicated that cutting bill requirements have a large influence on yield when the shortest part length in the bill is changed. Medium-length part sizes also affect yield except when the cutting bill requires an unlimited number of small parts; in this case, yield always will be high. When an all-blades-movable arbor is used, length changes in the bill affect yield more than changes in width. This study reveals our current lack of understanding of the complex relationship between cutting bill and lumber yield, and points out the yield gains that are possible when properly designed cutting bills are used

The Influence of Cutting-Bill Requirements on Lumber Yield Using a Fractional-Factorial Design Part II. Correlation and Number of Part Sizes

Cutting-bill requirements, among other factors, influence the yield obtained when cutting lumber into parts. The first part of this 2-part series described how different cutting-bill part sizes, when added to an existing cutting-bill, affect lumber yield, and quantified these observations. To accomplish this, the study employed linear least squares estimation technique. This second paper again looks at the influence of cutting-bill requirements but establishes a measure of how preferable it is to have a given part size required by the cutting-bill. The influence of the number of different part sizes to be cut simultaneously on lumber yield is also investigated.Using rip-first rough mill simulation software and an orthogonal, 220-11 fractional-factorial design of resolution V, the correlation between lengths, widths, and 20 part sizes as defined by the Buehlmann cutting-bill with high yield was established. It was found that, as long as the quantity of small parts is limited, part sizes larger than the smallest size are more positively correlated with high yield. Furthermore, only 4 out of the 20 part sizes tested were identified with having a significant positive correlation with above average yield (65.09%), while 10 were found with a significant negative correlation and above average yield. With respect to the benefit of cutting varying numbers of part sizes simultaneously, this study showed that there is a positive correlation between yield and the number of different part sizes being cut. However, Duncan's test did not detect significant yield gains for instances when more than 11 part sizes are contained in the cutting-bill

Creating A Standardized and Simplified Cutting Bill Using Group Technology

From an analytical viewpoint, the relationship between rough mill cutting bill part requirements and lumber yield is highly complex. Part requirements can have almost any length, width, and quantity distribution within the boundaries set by physical limitations, such as maximum length and width of parts. This complexity makes it difficult to understand the specific relationship between cutting bill requirements and lumber yield, rendering the optimization of the lumber cutting process through improved cutting bill composition difficult.An approach is presented to decrease the complexity of cutting bills to allow for easier analysis and, ultimately, to optimize cutting bill compositions. Principles from clustering theory were employed to create a standardized way to describe cutting bills. Cutting bill part clusters are part groups within the cutting bill's total part size space, where all parts are reset to a given group's midpoint. Statistical testing was used to determine a minimum resolution part group matrix that had no significant influence on yield compared to an actual cutting bill.Iterative search led to a cutting bill part group matrix that encompasses five groups in length and four groups in width, forming a 20-part group matrix. The lengths of the individual part groups created vary widely, with the smallest group being only 5 inches in length, while the longest two groups were 25 inches long. Part group widths were less varied, ranging from 0.75 inches to 1.0 inch. The part group matrix approach allows parts to be clustered within given size ranges to one part group midpoint value without changing cut-up yield beyond set limits. This standardized cutting bill matrix will make the understanding of the complex cutting bill requirements-yield relationship easier in future studies

Validation of the Standardized and Simplified Cutting Bill

This research validated the framework for the standardized and simplified cutting bill presented in an earlier paper. The cutting bill validation was carried out in two ways. First, all 20 of the cutting bill's part groups were examined to determine if significant yield influences resulted from changing specific part sizes within the boundaries of a given part group. Second, five cutting bills from industrial operations were fit into the framework of the cutting bill, and the simulated yields from these industrial cutting bills were compared with the fitted cutting bills. Yield differences between the two were calculated and tested for significance. Tests revealed that the standardized and simplified cutting bill framework performed as designed. The maximum yield difference observed was 2% and the average less than 1%. Clustering the industrial cutting bill part requirements according to the cutting bill framework led to an average absolute yield deviation between the original cutting bills and the clustered cutting bills of 3.25%. These results show while cutting bill part-size requirements can be clustered into part groups, yield differences of a certain magnitude are introduced by so doing

The Influence of Cutting-Bill Requirements on Lumber Yield Using a Fractional-Factorial Design Part I. Linearity and Least Squares

The importance of lumber yield on the financial success of secondary solid wood products manufacturers has been known for quite some time. Various efforts have been undertaken to improve yield, such as inclusion of character marks (defects) in parts, "cookie-cutting" of boards, improved optimization algorithms, or improved cut-up technologies. For a variety of reasons, the relationship between cutting-bill requirements and lumber yield has attracted limited attention. This is Part I of a 2-part examination of this relationship.The standardized and simplified Buehlmann cutting bill and the Forest Service's Romi-Rip lumber cut-up simulator were used in this study. An orthogonal, 220-11 fractional-factorial design of resolution V was used to determine the influence of different part sizes on lumber yield. All 20 part sizes contained in the cutting bill and 113 of a total of 190 unique secondary interactions were found to be significant variables in explaining the variability in observed yield. Parameter estimates for the part sizes and the secondary interactions were used to specify the average yield contribution of each variable. Parts 445 mm long and 64 mm wide were found to have the most positive influence on yield. Parts smaller than 445 by 64 mm (such as, for example 254 by 64 mm) had a less pronounced positive yield effect because their quantity requirement is relatively small in an average cutting bill. Thus, the quantity required is obtained quickly during the cut-up process. Parts with size 1842 by 108 mm, on the other hand, had the most negative influence on high yield. However, as further analysis showed, not only the individual parts required by a cutting bill, but also their interaction determines yield. In general, it was found that by adding a sufficiently large number of smaller parts to a cutting bill that required large parts, high levels of yield can be achieved

The Lean Index: Operational "Lean" Metrics for the Wood Products Industry

No standard definition for lean production exists today, especially specific to the wood products industries. From a management point of view, even the more straightforward management issues surrounding the concept of "lean" are complex. This exploratory research seeks to develop a methodology for quantitative and objective assessment of the leanness of any wood products operation. Factor analysis is a statistical approach that describes the patterns of relationships among quantifiable predictor variables, with the goal of identifying variables that cannot be directly measured, such as the leanness of a company. Using this technique, a factor model was identified and a factor score, or "Lean Index," was developed. For the nine wood products companies included in this study, the average Lean Index is demonstrated to be 5.07, ranging from a low of 2.33 to a high of 12.00. Based on the quantified standards of lean production developed in this study, (1) primary wood products operations are inherently leaner than secondary wood products operations; (2) process throughput variables explain approximately twice the total variance of all consumed resources, compared to process support variables; and (3) energy consumption is shown to be the single most significant contributor to the leanness of any wood products company

Air Permeability, Shrinkage, And Moisture Sorption of Lodgepole Pine Stemwood

The longitudinal air permeabilities, shrinkage (from fully swollen to oven-dry), and moisture sorption characteristics of two varieties (latifotia and murrayana) of lodgepole pine (Pinus contorta) were measured, based on wood samples taken from ten latitudes (37.5° to to 60°N) in western North America, from 279 trees of three diameter classes (76, 152, 228 mm DBH).The mean permeabilities of the sapwood and heartwood were 0.13 and 0.014 darcy, respectively. Geographical latitude and elevation of trees did not affect permeability. The mean calculated radius of pit pores in the sapwood was 1.5 μm, with median values between 12-13 pit pores per mm2. There was a fair correlation between water retention in an empirical water-soaking test and axial gas permeability.The volumetric and radial shrinkages, as well as the ratio of radial to tangential shrinkage, all increased with increasing specific gravity for both varieties. Tree size and latitude also affected shrinkage somewhat, primarily through their effects on specific gravity. The mean ratio of percent volumetric shrinkage to specific gravity was 30.7 2.9% for the two varieties combined.The moisture sorption study gave adsorption and desorption equilibrium moisture content (EMC) values at 30 C at relative humidities of 34.4, 65.0, and 83.2% for both varieties, on each of 62 test samples, representing the three different tree sizes and nine different latitudes. The mean adsorption-desorption (A/D) ratio was 0.79. The EMCs generally decreased with increasing latitude, with no significant difference between varieties at corresponding latitudes

System Simulation Modeling: A Case Study Illustration of the Model Development Life Cycle

Systems simulation modeling techniques offer a method of representing the individual elements of a manufacturing system and their interactions. By developing and experimenting with simulation models, one can obtain a better understanding of the overall physical system. Forest products industries are beginning to understand the importance of simulation modeling to help improve the dynamic performance of their processing and manufacturing systems. However, much knowledge and expertise are needed to accurately represent an actual forest products processing system as a simulation model. The purpose of this paper is to describe some effective process simulation model development strategies. This description points to the depth and breadth of knowledge that are needed to create usable and valid simulation models. To assist in illustrating the simulation modeling life cycle, actual case studies in modeling furniture rough mills are used