The New Zealand forest industry produces a diverse range of log grades and sorts to meet domestic and export market demands and to maximise returns to the forest grower. An implication for the supply chain is the number of log grades and sorts a harvesting operation is expected to produce from one species, radiata pine (Pinus radiata). The number of log grades and sorts can impact on landing size and layout requirements, value recovery, log-making complexity, machine utilisation and quality control requirements. A study was conducted to investigate if the number of log sorts affects mechanised log processing productivity and value recovery. This would determine if any gross value gains derived from producing a higher number of sorts are offset by losses in log processing productivity. Two landing-based mechanised log processors at cable yarder harvesting operations were studied using different cutting scenarios producing five, nine, twelve and fifteen log sorts. The study collected data from over 26 hours of mechanised processing which included the processing of 578 stems at an average piece size of approximately 1.6 m³. Machine utilisation results showed processors spending 84% of total time on productive tasks and that 49% of total time was spent on the primary productive tasks of log processing. Quadratic regressions were used to model log processing productivity trends which showed piece size and cutting scenario as significant predictor variables (p-value <0.01). There was a significant difference between cutting scenario with five log sorts and the cutting scenarios with twelve and fifteen log sorts (p-values <0.05), as well as a significant difference between the nine and fifteen log sort cutting scenarios (p-value <0.01). There was not enough evidence to suggest productivity was different between cutting scenarios producing five and nine log sorts. Based on this analysis, it was likely that the null hypothesis that the number of log sorts does not affect log processing productivity should be rejected. At a piece size of 2 m³, the productivity model estimated processing productivity was 10% higher producing nine log sorts compared to producing fifteen log sorts. A linear regression model showed a strong relationship between gross value recovery, piece size and cutting scenario (p-value <0.01). Gross value recovery increased as the number of log sorts increased. A significant model suggested it is likely null hypothesis 2, that the number of log sorts does not affect gross value recovery, should be rejected. There were only some differences in variances between cutting scenarios which were statistically significant. Both the average results and regression estimates showed the five log sort cutting scenario recovering 94% of the value of the cutting scenario with fifteen log sorts. Incremental gains in value recovery as the number of log sorts increased were marginal, which appeared to be due to log prices for many major log grades trading in a close range in relation to historic price trends. Regression trends for productivity and gross value recovery indicated that the most optimal cutting scenario, in terms of processing value outturn per productive machine hour, was the cutting scenario producing nine log sorts. This suggests that declines in processor productivity offset gains in gross value recovery when producing twelve and fifteen log sorts. Market sensitivity analysis suggested that differentials in log prices impact on the number of log sorts which optimise the value outturn per productive machine hour from log processing.

The prolonged challenges and dire consequences of poor sanitation, especially in developing economies, call for the exploration of new sustainable technologies. These need to be: capable of effectively treating human faecal wastes without any health or environmental impacts; scalable to address rapid increases in population and urbanization; capable of meeting environmental regulations and standards for faecal management; and competitive with existing strategies. Further and importantly, despite its noxiousness and pathogenic load, the chemical composition of human biowaste (HBW) indicates that it may be considered to be a potentially valuable, nutrient-rich renewable resource, rather than a problematic waste product. This doctoral study therefore investigated microwave hydrothermal carbonization (M-HTC) as a sanitation technology for processing HBW - to convert it into a safe, pathogen-free material, while also recovering inherent value and providing an economic base to sustain the technology. To this end, the products of M-HTC treatment of sewage sludge, human faecal sludge, synthetic faecal simulant and human faeces were characterized with a suite of techniques and tests to demonstrate pathogenic deactivation, and the intrinsic value of the resultant solid char and liquor.

This dissertation addresses gaps in the interaction between End-of-Life (EoL) product acquisition systems and disassembly sequencing. The research focuses on two remanufacturing research problems; 1) modeling uncertain EoL product quality, quantity, and timing in regards to EoL product acquisition and disassembly sequencing and 2) designing EoL product acquisition schemes considering EoL product uncertainty. The main research objectives within these areas are; analyzing, predicting, and controlling EoL product uncertainty, and incorporating EoL product uncertainty into operational and strategic level decisions. This research addresses these objectives by researching a methodology to determine optimal or near-optimal partial disassembly sequences using infeasible sequences while considering EoL product quality uncertainty. Consumer incentives are integrated into the methodology to study the effect of EoL product take-back incentives, but it also allows for the study of EoL product quantity uncertainty. EoL product age distributions are key to integrating the disassembly sequence method with EoL product acquisition management, acting both as an indicator of quality and as a basis for determining return quantity when considering incentives. At a broader level, this research makes it possible to study the impact of EoL product quality, and to an extent quantity, uncertainty resulting from strategic level (acquisition scheme) decisions, on operational (disassembly sequencing) decisions. This research is motivated by the rising importance of value recovery and sustainability to manufacturers. Extended Producer Responsibility (EPR) and Product Stewardship (PS) policies are, globally, changing the way products are treated during their use-life and EoL. Each new policy places a greater responsibility on consumers and manufacturers to address the EoL of a product. Manufacturers, in particular, may have to fulfill these obligations by such means as contracting 3rd parties for EoL recovery or performing recovery in-house. The significance of this research is linked to the growing presence of remanufacturing and recovery in the US and global economy, either via profitable ventures or environmental regulations. Remanufacturing, in particular, was surveyed by the US International Trade Commission in 2011-2012, where it was determined that remanufacturing grew by 15% to $43 billion, supported 180,000 full-time jobs from 2009-2011, and is continuing to grow. A partial disassembly sequence, multi-objective genetic algorithm (GA) is used a solution procedure to address the problem of determining the optimal or near-optimal partial disassembly sequence considering a continuous age distribution of EoL or available consumer products, with and without a consumer take-back incentive. The multi-objective GA, novel to the presented approach, relies on infeasible sequences to converge to optimal or near-optimal disassembly sequences. It is verified with a discrete economic and environmental impact case prior to incorporating EoL product age distributions. Considering the age distribution of acquired EoL products allows for decisions to be made based not only on expected profit, but also on profit variance and profit probability per EoL product, which was not observed in previous literature. As such, the research presented here within provides three contributions to disassembly and EoL product acquisition research: 1) integrating EoL product age distributions into partial disassembly sequencing objective functions, 2) accounting for partial disassembly sequence expected profit, profit variation, and profit probability as compared to disassembly sequencing methods that have, historically, only considered expected profit, and 3) studying the impact of EoL product age distributions and consumer take-back incentives on optimal or near-optimal partial disassembly sequences. Overall, this doctoral research contributes to the body of knowledge in value recovery, reverse logistics, and disassembly research fields, and is intended to be used, in the future, to develop and design efficient EoL product acquisition systems and disassembly operations. / Ph. D.

The purpose of this research was to quantify what value could be gained from cutting solid wood products from old-growth western hemlock (Tsuga heterophylla (Raf.) Sarg.) logs that are used to produce pulp in British Columbia. These logs represent a significant portion of the resource and increasing their value recovery would be beneficial to the forest industry. One hundred and sixteen logs were sampled from the coastal and interior regions of British Columbia. Dimension and quality attributes were measured to enable estimates of gross and merchantable volume. Logs deemed likely to yield lumber were sawn with the aim of maximizing value recovery. The nominal dimension and grade of all lumber recovered was recorded. Margins and breakpoints at which sawing became profitable were calculated. Models to predict the volume of lumber and proportion of Clear grade lumber recovered (“C Industrial” grade at the interior mill, “D Select” grade at the coastal mill) were developed. Lumber recovery, especially Clear grade lumber, was significantly higher from logs from the coastal site. At current market prices, cutting lumber from these logs was profitable, with the highest margins achieved when chips were produced from the milling residue. It was not profitable to recover lumber from the interior logs regardless of whether chips were produced. The disparity between locations was attributed to differences between the logs, the sawmilling equipment, the sawyers’ motivations and the lumber grades. Between 60% and 67% of coastal logs and 13% to 21% of interior logs returned a profit, depending on whether chips were produced. Models were developed to better identify these logs using observable attributes. A linear model described the total volume of lumber recovered. Significant predictor variables in the model were the gross log volume, the average width of the sound collar and the stage of butt/heart rot at the large end. A second model predicted the proportion of Clear grade lumber. Regional models were developed to account for different Clear lumber grades between sawmills. Significant predictor variables were knot frequency, diameter at the large end, volume, length, taper and the width of the sound collar at the large end.

The purpose of this research was to quantify what value could be gained from cutting solid wood products from old-growth western hemlock (Tsuga heterophylla (Raf.) Sarg.) logs that are used to produce pulp in British Columbia. These logs represent a significant portion of the resource and increasing their value recovery would be beneficial to the forest industry. One hundred and sixteen logs were sampled from the coastal and interior regions of British Columbia. Dimension and quality attributes were measured to enable estimates of gross and merchantable volume. Logs deemed likely to yield lumber were sawn with the aim of maximizing value recovery. The nominal dimension and grade of all lumber recovered was recorded. Margins and breakpoints at which sawing became profitable were calculated. Models to predict the volume of lumber and proportion of Clear grade lumber recovered (“C Industrial” grade at the interior mill, “D Select” grade at the coastal mill) were developed. Lumber recovery, especially Clear grade lumber, was significantly higher from logs from the coastal site. At current market prices, cutting lumber from these logs was profitable, with the highest margins achieved when chips were produced from the milling residue. It was not profitable to recover lumber from the interior logs regardless of whether chips were produced. The disparity between locations was attributed to differences between the logs, the sawmilling equipment, the sawyers’ motivations and the lumber grades. Between 60% and 67% of coastal logs and 13% to 21% of interior logs returned a profit, depending on whether chips were produced. Models were developed to better identify these logs using observable attributes. A linear model described the total volume of lumber recovered. Significant predictor variables in the model were the gross log volume, the average width of the sound collar and the stage of butt/heart rot at the large end. A second model predicted the proportion of Clear grade lumber. Regional models were developed to account for different Clear lumber grades between sawmills. Significant predictor variables were knot frequency, diameter at the large end, volume, length, taper and the width of the sound collar at the large end.

The purpose of this research was to quantify what value could be gained from cutting solid wood products from old-growth western hemlock (Tsuga heterophylla (Raf.) Sarg.) logs that are used to produce pulp in British Columbia. These logs represent a significant portion of the resource and increasing their value recovery would be beneficial to the forest industry. One hundred and sixteen logs were sampled from the coastal and interior regions of British Columbia. Dimension and quality attributes were measured to enable estimates of gross and merchantable volume. Logs deemed likely to yield lumber were sawn with the aim of maximizing value recovery. The nominal dimension and grade of all lumber recovered was recorded. Margins and breakpoints at which sawing became profitable were calculated. Models to predict the volume of lumber and proportion of Clear grade lumber recovered (“C Industrial” grade at the interior mill, “D Select” grade at the coastal mill) were developed. Lumber recovery, especially Clear grade lumber, was significantly higher from logs from the coastal site. At current market prices, cutting lumber from these logs was profitable, with the highest margins achieved when chips were produced from the milling residue. It was not profitable to recover lumber from the interior logs regardless of whether chips were produced. The disparity between locations was attributed to differences between the logs, the sawmilling equipment, the sawyers’ motivations and the lumber grades. Between 60% and 67% of coastal logs and 13% to 21% of interior logs returned a profit, depending on whether chips were produced. Models were developed to better identify these logs using observable attributes. A linear model described the total volume of lumber recovered. Significant predictor variables in the model were the gross log volume, the average width of the sound collar and the stage of butt/heart rot at the large end. A second model predicted the proportion of Clear grade lumber. Regional models were developed to account for different Clear lumber grades between sawmills. Significant predictor variables were knot frequency, diameter at the large end, volume, length, taper and the width of the sound collar at the large end. / Forestry, Faculty of / Graduate

A company's decisions on how to manage its reverse supply chain (RSC) are important for both economic and environmental reasons. From a strategic standpoint, the key decision a manufacturer makes is whether or not to collect products at their end-of-life (EOL) (i.e., when their useful lives are over), and if so, how to recover value from the recovered products. We call this decision as the EOL option of a product, and it determines how the RSC is designed and managed overall. Many EOL options exist for a product such as resale, refurbishment, remanufacturing and part salvage. However, many factors influence the optimal EOL option. These factors include the product's: (i) characteristics, (ii) design, and (iii) pricing. A product's characteristics are its properties that impact the various costs incurred during its production, residual part values, and customer demand. In this work, the product design is viewed as the choice of quality for each of its parts. A part's quality-level determines, among other things, its cost, salvage value, and the likelihood of obtaining it in good condition from a disassembled used product. Finally, the manufacturer must determine how to price its new and used products. This decision depends on many considerations such as whether new and used products compete and whether competition exists from other manufacturers. The choice of appropriate EOL options for products constitutes a foundation of RSC design. In this work, we study how to optimally determine a product's optimal EOL option and consider the impact of product design and product pricing on this decision. We present a full description of the system that details the relationships among all entities. The system description reveals the use of a production planning type of modeling strategy. Additionally, a comprehensive and general mathematical model is presented that takes into consideration multi-period planning and product inventory. A unique aspect of our model over previous production planning models for RSC is that we consider the product returns as being endogenous variables rather than them being exogenous. This model forms the basis of our research, and we use its special cases in our analysis. To begin our analysis of the problem, we study the case in which the product design and price are fixed. Both non-mandated and mandated collection are considered. Our analysis focuses on a special case of the problem involving two stages: in the first stage, new products are produced, and in the second stage, the EOL products are collected for value recovery. For fixed product design and price, our analysis reveals a fundamental mapping of product characteristics onto optimal EOL options. It is germane to our understanding of the problem in general since a multi-period problem is separable into multiple two-stage problems. Necessary and sufficient optimality conditions are also presented for each possible solution of this two-stage problem. For the two-part problem, a graphical mapping of product characteristics onto optimal EOL options is also presented, which reveals how EOL options vary with product characteristics. Additionally, we study the case of product design under mandated collection, as encountered in product leasing. We assume new production cost, part replacement cost, and part salvage value to be functions of the quality-level of a part along with the likelihood of recovering a good-part from a returned product. These are reasonable assumptions for leased products since the customer is paying for the usage of the product over a fixed contract period. In this case, the two-stage model can still be used to gain insights. For the two-part problem, a method for mapping part yields onto optimal EOL options is presented. Closed-form optimality conditions for joint determination of part yields and EOL options are not generally attainable for the two-stage case; however, computationally efficient methods for this problem are developed for some relatively non-restrictive special cases. It is found that, typically, a part may belong to one of three major categories: (i) it is of low quality and will need to be replaced to perform remanufacturing, (ii) it is of high quality and its surplus will be salvaged, or (iii) it is of moderate quality and just enough of its amount is collected to meet remanufactured product demand. Finally, we consider the problem of determining optimal prices for new and remanufactured products under non-mandated manufacturer's choice of collection. New and remanufactured products may or may not compete, depending on market conditions. Additionally, we assume the manufacturer to have a monopoly on the product. Again, the two-stage problem is used and efficient solution methods are developed. Efficient solution methods and key insights are presented. / Ph. D.

Three independent case studies focused on harvesting operation value improvement: (1) A productivity study was carried out on a new cable logging operation near Pikeville, Kentucky to document the effect of professional training on production efficiency. The crew received one full week of professional training. Prior to the professional training the productivity of the operation was established at 834 cubic feet per productive machine hour at an average piece size of 54 cubic feet. Two weeks after the training a productivity increase of 218 cubic feet per productive machine hour was established. (2) A USDA Forest Service stewardship contracting pilot project took place at Burns' Creek, Virginia. Productivity and machine costs for the cable-logging 'swing landing' operation were determined. Stream habitat improvement was achieved through the placement of limestone in the headwaters. The yarder placed 6.21 tons of lime per productive machine hour into the creek at a cost of $53 per ton. Instead of a traditional stumpage sale, timber was merchandized by the Forest Service and stored on the landing for a roadside log sale. Benefits and opportunities for a roadside log sale were identified. Consensus from the consumers at the log-sale was that the potential value of the timber was realized. (3) The third case study involved the analysis of the value recovered through log-making techniques (bucking) for five logging crews working in Virginia and West Virginia. An average value loss of 22 percent was calculated using the HW-BUCK bucking optimizer software package. <i>[Vita removed March 2011. GMc]</i> / Master of Science

abstract: This dissertation presents a novel algorithm for recovering missing values of co-evolving time series with partial embedded network information. The idea is to connect two sources of data through a shared low dimensional latent space. The proposed algorithm, named NetDyna, is an Expectation-Maximization algorithm, and uses the Kalman filter and matrix factorization approaches to infer the missing values both in the time series and embedded network. The experimental results on real datasets, including a Motes dataset and a Motion Capture dataset, show that (1) NetDyna outperforms other state-of-the-art algorithms, especially with partially observed network information; (2) its computational complexity scales linearly with the time duration of time series; and (3) the algorithm recovers the embedded network in addition to missing time series values. This dissertation also studies a load balancing algorithm, the so called power-of-two-choices(Po2), for many-server systems (with N servers) and focuses on the convergence of stationary distribution of Po2 in the both light and heavy traffic regimes to the solution of mean-field system. The framework of Stein’s method and state space collapse (SSC) are used to analyze both regimes. In both regimes, the thesis first uses the argument of state space collapse to show that the probability of the state being far from the mean-field solution is small enough. By a simple Markov inequality, it is able to show that the probability is indeed very small with a proper choice of parameters. Then, for the state space close to the solution of mean-field model, the thesis uses Stein’s method to show that the stochastic system is close to a linear mean-field model. By characterizing the generator difference, it is able to characterize the dominant terms in both regimes. Note that for heavy traffic case, the lower and upper bound analysis of a tridiagonal matrix, which arises from the linear mean-field model, is needed. From the dominant term, it allows to calculate the coefficient of the convergence rate. In the end, comparisons between the theoretical predictions and numerical simulations are presented. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2020

The rapid increase in clothing consumption over the last decades has meant a significant burden on the environment. Some examples of this are the high consumption of natural resources and land, increasing amounts of carbon emissions, excessive use of toxic chemicals, polluting air, land and water and increasing amounts of waste. The average clothing consumption in Europe is far higher than the world average, especially in Nordic countries including Sweden. Adopting and encouraging more circular economies is a part of the European commission‘s strategy to achieve sustainable consumption of resources and protection for environment. The purpose of this Research is to study the possibilities of improving the practice of second hand clothes consumption in Sweden and make it more effective towards the goal of sustainable consumption and circular economies. In order to achieve this goal, it is necessary to understand the challenges and find abilities for improvement in the value chain of used clothes in Sweden, with focus on the reverse logistics system of used clothes (collection and sorting processes) as well as the market of second hand clothes. In order to achieve the purpose of the study, the conceptual framework has been formulated upon studying relevant literature and results of previous studies. Value chains of three charity organizations have been studied and empirical data have been collected through semi-structured interviews with participants from these three organizations. The empirical findings have been interpreted in relation to the conceptual framework and the results of previous studies, in order to answer the research questions. The results of the study showed potential for improvement and development in the reverse logistics system (collections and sorting processes) of used clothes, as well as in the Swedish market of second hand clothes. However, benefiting of this potential requires collaboration between all stakeholders in the value chain of used clothes, including individuals (either in a position of donors or consumers), interested businesses (nonprofit or commercial organizations), government, municipalities, politicians and finally the private sector in clothing industry.