A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

Strategic supply chain management factors influencing agribusiness innovation utilization

Purpose – The purpose of this paper is to examine empirically, an industry development paradox, using embryonic literature in the area of strategic supply chain management, together with innovation management literature. This study seeks to understand how, forming strategic supply chain relationships, and developing strategic supply chain capability, influences beneficial supply chain outcomes expected from utilizing industry-led innovation, in the form of electronic business solutions using the internet, in the Australian beef industry. Findings should add valuable insights to both academics and practitioners in the fields of supply chain innovation management and strategic supply chain management, and expand knowledge to current literature. Design/methodology/approach – This is a quantitative study comparing innovative and non-innovative supply chain operatives in the Australian beef industry, through factor analysis and structural equation modeling using PAWS Statistical V18 and AMOS V18 to analyze survey data from 412 respondents from the Australian beef supply chain. Findings – Key findings are that both innovative and non-innovative supply chain operators attribute supply chain synchronization as only a minor indicator of strategic supply chain capability, contrary to the literature; and they also indicate strategic supply chain capability has a minor influence in achieving beneficial outcomes from utilizing industry-led innovation. These results suggest a lack of coordination between supply chain operatives in the industry. They also suggest a lack of understanding of the benefits of developing a strategic supply chain management competence, particularly in relation to innovation agendas, and provides valuable insights as to why an industry paradox exists in terms of the level of investment in industry-led innovation, vs the level of corresponding benefit achieved. Research limitations/implications – Results are not generalized due to the single agribusiness industry studied and the single research method employed. However, this provides opportunity for further agribusiness studies in this area and also studies using alternate methods, such as qualitative, in-depth analysis of these factors and their relationships, which may confirm results or produce different results. Further, this study empirically extends existing theoretical contributions and insights into the roles of strategic supply chain management and innovation management in improving supply chain and ultimately industry performance while providing practical insights to supply chain practitioners in this and other similar agribusiness industries. Practical implications – These findings confirm results from a 2007 research (Ketchen et al., 2007) which suggests supply chain practice and teachings need to take a strategic direction in the twenty-first century. To date, competence in supply chain management has built up from functional and process orientations rather than from a strategic perspective. This study confirms that there is a need for more generalists that can integrate with various disciplines, particularly those who can understand and implement strategic supply chain management. Social implications – Possible social implications accrue through the development of responsible government policy in terms of industry supply chains. Strategic supply chain management and supply chain innovation management have impacts to the social fabric of nations through the sustainability of their industries, especially agribusiness industries which deal with food safety and security. If supply chains are now the competitive weapon of nations then funding innovation and managing their supply chain competitiveness in global markets requires a strategic approach from everyone, not just the industry participants. Originality/value – This is original empirical research, seeking to add value to embryonic and important developing literature concerned with adopting a strategic approach to supply chain management. It also seeks to add to existing literature in the area of innovation management, particularly through greater understanding of the implications of nations developing industry-wide, industry-led innovation agendas, and their ramifications to industry supply chains.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Growth and characterization of pure and doped single crystals of $CuGeO_{3}$

Good quality single crystals of copper metagermanite, CuGeO3, are grown by flux technique. Growth is carried out at relatively low temperatures by using Bi2O3 along with CuO in an optimal flux ratio. Besides rendering the procedure simple, lower growth temperature reduces growth defect concentration. Single crystals of Cu1 - xCoxGeO3 and CuGe1 - yGayO3 are grown by the same method for different values of x and y to investigate the influence of in-chain and off-chain doping on spin-Peierls (SP) transition. Change in color, morphology and surface features as a result of doping are briefly discussed. Spin-Peierls transition of these crystals is studied by susceptibility measurements on a commercial SQUID magnetometer. Cationic substitution resulted in reduction of spin-Peierls transition temperature (T-SP) of CuGeO3. Substitution of magnetic impurity cobalt in-chain site caused more pronounced effects such as suppression of SP phase.

Influence of cobalt doping on superconducting transition in as-grown YBCO single crystals

The role of a charge buffer layer in the superconductivity of high-T-c materials is best studied by cationic substitutions. In this work, the chain copper in YBCO single crystals is substituted by Co3+ ion and consequent effect on superconducting transition temperature (T-c) studied. The T-c is measured using non-resonant Microwave Absorption technique, which is a highly sensitive and contactless method. It is seen that T-c of as-grown crystals is considerably enhanced by cobalt doping in low concentration regime. In contrast, higher T-c is achieved in undoped crystals only after extended oxygen anneal. When dopant concentration increases beyond an optimal value, T-c decreases and the system does not show superconductivity when cobalt content is high (x > 0.5 in YBa2Cu3-xCOxO7+/-delta). This behaviour consequent to cobalt substitution is discussed with reference to the apical oxygen model. Optimal cobalt doping can be thought of as an alternative to extended oxygen anneal in as-grown crystals of YBCO.

Genetic variability of Tomato spotted wilt virus in Australia and validation of real time RT-PCR for its detection in single and bulked leaf samples

The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy® or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to 1 infected in 800 samples with pepper but never detecting more than 1 infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.

Self-assembly of three new coordination complexes: Formation of 2-D square grid, 1-D chain and tape structures

Three distinct coordination complexes, viz., [Co(imi)(2)(tmb)(2)] (1) [where imi = imidazole], {[Ni(tmb)(2)(H2O)(3)]center dot 2H(2)O}(n) (2) and [Cu-2(mu-tmb)(4)(CH3OH)(2)] (3), have been synthesized hydrothermally by the reactions of metal acetates,2,4,6-trimethylbenzoic acid (Htmb) and with or without appropriate amine. The Ni analogue of 1 and the Co analogue of 2 have also been synthesized. X-ray single-crystal diffraction suggests that complex 1 represents discrete mononuclear species and complex 2 represents a 1D chain coordination polymer in which the Ni(H) ions are connected by the bridging water molecules. Complex 3 represents a neutral dinuclear complex. In 1, the central metal ions are associated by the carboxylate moiety and imidazole ligands, whereas the central metal atom is coordinated to the carboxylate moiety and the respective solvent molecules in 2 and 3. In 3, the four 2,4,6-trimethylbenzoate moieties act as a bridge connecting two copper (11) ions and the 0 atoms of methanol coord geometry, with the methanol molecule at the apical position. In all the three structures the central metal atom sits on a crystallographic inversion centre. In all the cases, the coordination entities are further organized via hydrogen bonding interactions to generate multifarious supramolecular networks. Complexes 1, 2 and 3 have also been characterized by spectroscopic (UV/Vis and IR) and thermal analysis (TGA). In addition, the complexes were found to exhibit antimicrobial activity. The magnetic susceptibility measurements, measured from 8 to 300 K, revealed antiferromagnetic interactions between the Co(II) ions in compound 1 and the Ni(II) ions in la, respectively.

Understanding the organic chain : The framework of the interaction between the actors in organic chains in relation to ecological modernisation of food production

The sustainability of food production has increasingly attracted the attention of consumers, farmers, food and retailing companies, and politicians. One manifestation of such attention is the growing interest in organic foods. Organic agriculture has the potential to enhance the ecological modernisation of food production by implementing the organic method as a preventative innovation that simultaneously produces environmental and economic benefits. However, in addition to the challenges to organic farming, the small market share of organic products in many countries today and Finland in particular risks undermining the achievement of such benefits. The problems identified as hindrances to the increased consumption of organic food are the poor availability, limited variety and high prices of organic products, the complicated buying decisions and the difficulties in delivering the intangible value of organic foods. Small volumes and sporadic markets, high costs, lack of market information, as well as poor supply reliability are obstacles to increasing the volume of organic production and processing. These problems shift the focus from a single actor to the entire supply chain and require solutions that involve more interaction among the actors within the organic chain. As an entity, the organic food chain has received very little scholarly attention. Researchers have mainly approached the organic chain from the perspective of a single actor, or they have described its structure rather than the interaction between the actors. Consequently, interaction among the primary actors in organic chains, i.e. farmers, manufacturers, retailers and consumers, has largely gone unexamined. The purpose of this study is to shed light on the interaction of the primary actors within a whole organic chain in relation to the ecological modernisation of food production. This information is organised into a conceptual framework to help illuminate this complex field. This thesis integrates the theories and concepts of three approaches: food system studies, supply chain management and ecological modernisation. Through a case study, a conceptual system framework will be developed and applied to a real life-situation. The thesis is supported by research published in four articles. All examine the same organic chains through case studies, but each approaches the problem from a different, complementary perspective. The findings indicated that regardless of the coherent values emphasising responsibility, the organic chains were loosely integrated to operate as a system. The focus was on product flow, leaving other aspects of value creation largely aside. Communication with consumers was rare, and none of the actors had taken a leading role in enhancing the market for organic products. Such a situation presents unsuitable conditions for ecological modernisation of food production through organic food and calls for contributions from stakeholders other than those directly involved in the product chain. The findings inspired a revision of the original conceptual framework. The revised framework, the three-layer framework , distinguishes the different layers of interaction. By gradually enlarging the chain orientation the different but interrelated layers become visible. A framework is thus provided for further research and for understanding practical implications of the performance of organic food chains. The revised framework provides both an ideal model for organic chains in relation to ecological modernisation and demonstrates a situation consistent with the empirical evidence.

Stretching single DNA-molecules with temperature-stabilized optical tweezers

This thesis consists of two parts; in the first part we performed a single-molecule force extension measurement with 10kb long DNA-molecules from phage-λ to validate the calibration and single-molecule capability of our optical tweezers instrument. Fitting the worm-like chain interpolation formula to the data revealed that ca. 71% of the DNA tethers featured a contour length within ±15% of the expected value (3.38 µm). Only 25% of the found DNA had a persistence length between 30 and 60 nm. The correct value should be within 40 to 60 nm. In the second part we designed and built a precise temperature controller to remove thermal fluctuations that cause drifting of the optical trap. The controller uses feed-forward and PID (proportional-integral-derivative) feedback to achieve 1.58 mK precision and 0.3 K absolute accuracy. During a 5 min test run it reduced drifting of the trap from 1.4 nm/min in open-loop to 0.6 nm/min in closed-loop.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Inter-helical Interactions in Membrane Proteins: Analysis Based on the Local Backbone Geometry and the Side Chain Interactions

The availability of a significant number of the Structures of helical membrane proteins has prompted us to investigate the mode of helix-helix packing. In the present study, we have considered a dataset of alpha-helical membrane proteins representing Structures solved from all the known superfamilies. We have described the geometry of all the helical residues in terms of local coordinate axis at the backbone level. Significant inter-helical interactions have been considered as contacts by weighing the number of atom-atom contacts, including all the side-chain atoms. Such a definition of local axis and the contact criterion has allowed us to investigate the inter-helical interaction in a systematic and quantitative manner. We show that a single parameter (designated as alpha), which is derived from the parameters representing the Mutual orientation of local axes, is able to accurately Capture the details of helix-helix interaction. The analysis has been carried Out by dividing the dataset into parallel, anti-parallel, and perpendicular orientation of helices. The study indicates that a specific range of alpha value is preferred for interactions among the anti-parallel helices. Such a preference is also seen among interacting residues of parallel helices, however to a lesser extent. No such preference is seen in the case of perpendicular helices, the contacts that arise mainly due to the interaction Of Surface helices with the end of the trans-membrane helices. The Study Supports the prevailing view that the anti-parallel helices are well packed. However, the interactions between helices of parallel orientation are non-trivial. The packing in alpha-helical membrane proteins, which is systematically and rigorously investigated in this study, may prove to be useful in modeling of helical membrane proteins.

Mixed saturated-unsaturated alkyl-chain assemblies: Solid solutions of zinc stearate and zinc oleate

The linear saturated stearic acid and the bent mono-unsaturated oleic acid do not mix and form solid solutions. However, the zinc salts of these acids can. From X-ray diffraction and DSC measurements we show that the layered zinc stearate and zinc oleate salts form a homogeneous solid solution at all composition ratios. The solid solutions exhibit a single melting endotherm, with the melting temperature varying linearly with composition but with the enthalpy change showing a minimum. By monitoring features in the infrared spectra that are characteristic of the global conformation of the hydrocarbon chain, and hence can distinguish between stearate and oleate chains, it is shown that solid solution formation is realized by the introduction of gauche defects in a fraction of the stearate chains that are then no longer linear. This fraction increases with oleate concentration. It has also been possible from the spectroscopic measurements to establish a quantitative relation between molecular conformational order and the thermodynamic enthalpy of melting of the solid solutions.

Chain structures in alkali metal borophosphates: synthesis and characterization of K3[BP3O9(OH)3] and Rb3[B2P3O11(OH)2]

Two new alkali metal borophosphates, K-3[BP(3)o(9)(OH)(3)] and Rb-3[B2P3O11(OH)(2)], were synthesized by applying solvothermal techniques using ethanol as solvent. The crystal structures were solved by means of single-crystal X-ray diffraction (K-3[BP3O9(OH)(3)], monoclinic, C2/c (No. 15), a = 2454.6(8) pm, b = 736.3(2) pm, c = 1406.2(4) pm, beta = 118.35(2)degrees, Z = 8; Rb-3[B2P3O11(OH)(2)], monoclinic, P2(1)/c (No. 14), a = 781.6(2) pm, b:= 667.3(2) pm, c = 2424.8(5) pm, beta = 92.88(1)degrees, Z = 4). Both crystal structures comprise borophosphate chain anions. While for the rubidium compound a loop-branched chain motif is found as common for most of the chain anions in alkali metal borophosphates, the crystal structure of the potassium phase comprises the first open-branched chain with the highest phosphate content found so far in this group of compounds. Both chain anions are Closely related to known anhydrous or hydrated phases, and the structural relations are discussed in terms of how the presence of OH groups and hydrogen bonds as well as number, charge, and size of charge balancing cations influence the 3D structural arrangement. The anionic entities are classified in terms of general principles of structural systematics for borophosphates.

Terahertz Spectroscopy of Single-Walled Carbon Nanotubes in a Polymer Film: Observation of Low-Frequency Phonons

We investigate the dielectric response of single-walled carbon nanotubes dispersed in poly(vinyl alcohol) matrix by using terahertz time domain spectroscopy. Frequency-dependent real and imaginary parts of the complex dielectric function are measured experimentally in the terahertz regime. The low-frequency phonons of carbon nanotubes, though predicted theoretically, are directly observed for the first time at frequencies 0.26, 0.60, and 0.85 THz. Further, a broad resonance is observed at 1.15 THz associated with the longitudinal acoustic mode of vibration of straight-chain segments of the long polymeric molecules in the film. The latter is observed at 1.24 THz for a pristine polymer film and has been used to derive the size of crystalline lamellae in the film.