Log classification in the hardwood timber industry: method and value analysis

Abstract

My infinite gratitude is also to my research advisor, Mr. Jean-Marc Frayret, who not only believed in me since the beginning, but also welcomed me in his research team, and encouraged me to follow my research. His experience and great knowledge has given him a wide vision to find the right track every time I was clueless. After the long sessions we spend finding solutions to these and many other dilemmas, I realized that more than a good teacher, he is a great human being. I am proud of have working with him. All my acknowledgements goes also to Francis Fournier and Jean McDonald of FP Innovationsfor guiding this research and for providing us the technical information necessary to understand and solve the puzzle we had three years ago when this journey begin.Finally, I'd like to thank the VCO NSERC network for the financial support and for all the research and networking activities that I had the opportunity to be part of, which gave me the chance to have a better vision of the forest products industry and its challenges. v RÉSUMÉ Les industries avec différentes entrées, telles que : l'industrie des produits forestiers (FPI), l'industrie minière ou l'industrie du recyclage, doivent faire face à l'incertitude de matière primaire, ce qui affecte leur capacité à prévoir le rendement de sortie. Pour régler ce problème, les industries peuvent réduire l'incertitude à la source, ou de planifier les opérations en tenant compte de l'incertitude. Dans le FPI, la première approche est généralement utilisée. Par exemple, l'industrie du bois d'oeuvre a implémenté des technologies de transformation sophistiquées pour adapter le processus du sciage aux caractéristiques des billes en utilisant la technologie de numérisation pour obtenir des informations précises sur l'état des travaux en cours de fabrication.Une autre approche pour réduire l'incertitude est la classification de matière primaire. Certaines caractéristiques spécifiques peuvent être mesurées à l'entrée pour classer la matière primaire et en conséquence, augmenter la certitude des attentes de production dans chaque classe. Toutefois, si le processus implique les journaux, les minerais des mines ou des papiers recyclés, la ABSTRACTIndustries with variable inputs, such as the forest product industry (FPI), the mining industry or the recycling industry, must cope with material uncertainty, which affects their ability to predict output yields. To deal with this, one can either reduce uncertainty at the source, or plan operations taking uncertainty into account. In the FPI, the first approach is generally used. For instance, the softwood lumber industry has adopted sophisticated transformation technologies that adapt sawing patterns to the log characteristic using scanners technology to acquire accurate information about work-in-process status. Another approach to reduce uncertainty is input material classification. Specific characteristics can be measured to classify input material and therefore reduce uncertainty within each class. However, whether the process involv...

Wood Products Manufacturing Optimization: A Survey

“…The selected studies exploring the economic profits of optimal decision-making processes can be generally divided into three groups: production efficiency improvement [16], [18], [19], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [20], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], energy cost savings [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], and space savings [53], [56], [82], [83], [84], [85], [86],…”

“…Environmental footprint reduction [16], [18], [19], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [20], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70] [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81] [53], [56], [82], [83], [84], [85], [86], [87] [99], [100], [101], [102],…”

“…Recently, some researchers are addressing this issue by offering alternative solutions which permit enormous savings in terms of costs such as a more compact design of machinery [53], streamlining equipment and processes [84], smart log selection and sorting [85], inventory control [86], [87], and smart manufacturing for avoiding over-production [56].…”

Profitability gain expectations for computed tomography of sawn logs

“…Oja et al (2004) stated the crucial impact of reliable log grading and showed the possible contribution of a CT to a more precise log classification. The advantages and disadvantages of variously detailed log classification strategies were shown by Gil and Frayret (2016). Possible effects of CT data were not taken into account in that study.…”

Monitoring the Quality and Quantity of Beechwood from Tree to Sawmill Product

“…on the forest where the wood is measured and handed over. Also, there have been numerous narrowly oriented studies on wood processing that have mainly focused on yield analysis and optimisation of wood processing from log to sawn timber (Šoškić and Milić 2005, Popadić et al 2014, Wade et al 1992, Cibecchini et al 2016, Muñoz et al 2013, Lundahl and Grönlund 2010, Gil 2014.…”