Maximising the manufacturer performance value through lean initiatives using cost based model

Numerous tools and techniques have been developed to eliminate or reduce waste and carry out lean concepts in the manufacturing environment. However, appropriate lean tools need to be selected and implemented in order to fulfil the manufacturer needs within their budgetary constraints. As a result, it is important to identify manufacturer needs and implement only those tools, which contribute maximum benefit to their needs. In this research a mathematical model is proposed for maximising the perceived value of manufacturer needs and developed a step-by-step methodology to select best performance metrics along with appropriate lean strategies within the budgetary constraints. With the help of a case study, the proposed model and method have been demonstrated.

A restrike waveform predictive model for shunt capacitor bank switching with point-on-wave recommendation

Circuit-breakers (CBs) are subject to electrical stresses with restrikes during capacitor bank operation. Stresses are caused by the overvoltages across CBs, the interrupting currents and the rate of rise of recovery voltage (RRRV). Such electrical stresses also depend on the types of system grounding and the types of dielectric strength curves. The aim of this study is to demonstrate a restrike waveform predictive model for a SF6 CB that considered the types of system grounding: grounded and non-grounded and the computation accuracy comparison on the application of the cold withstand dielectric strength and the hot recovery dielectric strength curve including the POW (point-on-wave) recommendations to make an assessment of increasing the CB remaining life. The simulation of SF6 CB stresses in a typical 400 kV system was undertaken and the results in the applications are presented. The simulated restrike waveforms produced with the identified features using wavelet transform can be used for restrike diagnostic algorithm development with wavelet transform to locate a substation with breaker restrikes. This study found that the hot withstand dielectric strength curve has less magnitude than the cold withstand dielectric strength curve for restrike simulation results. Computation accuracy improved with the hot withstand dielectric strength and POW controlled switching can increase the life for a SF6 CB.

Developing a research method to test a new first-order decision making model for the procurement of public sector major infrastructure

Given global demand for new infrastructure, governments face substantial challenges in funding new infrastructure and simultaneously delivering Value for Money (VfM). The paper begins with an update on a key development in a new early/first-order procurement decision making model that deploys production cost/benefit theory and theories concerning transaction costs from the New Institutional Economics, in order to identify a procurement mode that is likely to deliver the best ratio of production costs and transaction costs to production benefits, and therefore deliver superior VfM relative to alternative procurement modes. In doing so, the new procurement model is also able to address the uncertainty concerning the relative merits of Public-Private Partnerships (PPP) and non-PPP procurement approaches. The main aim of the paper is to develop competition as a dependent variable/proxy for VfM and a hypothesis (overarching proposition), as well as developing a research method to test the new procurement model. Competition reflects both production costs and benefits (absolute level of competition) and transaction costs (level of realised competition) and is a key proxy for VfM. Using competition as a proxy for VfM, the overarching proposition is given as: When the actual procurement mode matches the predicted (theoretical) procurement mode (informed by the new procurement model), then actual competition is expected to match potential competition (based on actual capacity). To collect data to test this proposition, the research method that is developed in this paper combines a survey and case study approach. More specifically, data collection instruments for the surveys to collect data on actual procurement, actual competition and potential competition are outlined. Finally, plans for analysing this survey data are briefly mentioned, along with noting the planned use of analytical pattern matching in deploying the new procurement model and in order to develop the predicted (theoretical) procurement mode.

Manipulating task constraints to improve tactical knowledge and collective decision-making in rugby union

In team sports such as rugby union, a myriad of decisions and actions occur within the boundaries that compose the performance perceptual- motor workspace. The way that these performance boundaries constrain decision making and action has recently interested researchers and has involved developing an understanding of the concept of constraints. Considering team sports as complex dynamical systems, signifies that they are composed of multiple, independent agents (i.e. individual players) whose interactions are highly integrated. This level of complexity is characterized by the multiple ways that players in a rugby field can interact. It affords the emergence of rich patterns of behaviour, such as rucks, mauls, and collective tactical actions that emerge due to players’ adjustments to dynamically varying competition environments. During performance, the decisions and actions of each player are constrained by multiple causes (e.g. technical and tactical skills, emotional states, plans, thoughts, etc.) that generate multiple effects (e.g. to run or pass, to move forward to tackle or maintain position and drive the opponent to the line), a prime feature in a complex systems approach to team games performance (Bar- Yam, 2004). To establish a bridge between the complexity sciences and learning design in team sports like rugby union, the aim of practice sessions is to prepare players to pick up and explore the information available in the multiple constraints (i.e. the causes) that influence performance. Therefore, learning design in training sessions should be soundly based on the interactions amongst players (i.e.teammates and opponents) that will occur in rugby matches. To improve individual and collective decision making in rugby union, Passos and colleagues proposed in previous work a performer- environment interaction- based approach rather than a traditional performer- based approach (Passos, Araújo, Davids & Shuttleworth, 2008).

Asymptotic and numerical results for a model of solvent-dependent drug diffusion through polymeric spheres

A model for drug diffusion from a spherical polymeric drug delivery device is considered. The model contains two key features. The first is that solvent diffuses into the polymer, which then transitions from a glassy to a rubbery state. The interface between the two states of polymer is modelled as a moving boundary, whose speed is governed by a kinetic law; the same moving boundary problem arises in the one-phase limit of a Stefan problem with kinetic undercooling. The second feature is that drug diffuses only through the rubbery region, with a nonlinear diffusion coefficient that depends on the concentration of solvent. We analyse the model using both formal asymptotics and numerical computation, the latter by applying a front-fixing scheme with a finite volume method. Previous results are extended and comparisons are made with linear models that work well under certain parameter regimes. Finally, a model for a multi-layered drug delivery device is suggested, which allows for more flexible control of drug release.

Car following model improvement for traffic safety metrics reproduction

Car Following models have a critical role in all microscopic traffic simulation models. Current microscopic simulation models are unable to mimic the unsafe behaviour of drivers as most are based on presumptions about the safe behaviour of drivers. Gipps model is a widely used car following model embedded in different micro-simulation models. This paper examines the Gipps car following model to investigate ways of improving the model for safety studies application. The paper puts forward some suggestions to modify the Gipps model to improve its capabilities to simulate unsafe vehicle movements (vehicles with safety indicators below critical thresholds). The result of the paper is one step forward to facilitate assessing and predicting safety at motorways using microscopic simulation. NGSIM as a rich source of vehicle trajectory data for a motorway is used to extract its relatively risky events. Short following headways and Time To Collision are used to assess critical safety event within traffic flow. The result shows that the modified proposed car following to a certain extent predicts the unsafe trajectories with smaller error values than the generic Gipps model.

Practical stability of approximating discrete-time filters with respect to model mismatch using relative entropy concepts

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Using local consistency assumption, the practical stability established is in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Significantly, these practical stability results do not require the approximating model to be of the same model type as the true system. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical VC dimension, empirical VC entropy, and margin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

Partial protection against chlamydial reproductive tract infection by a recombinant major outer membrane protein/CpG/cholera toxin intranasal vaccine in the guinea pig Chlamydia cavaie model

Chlamydia trachomatis is a major cause of sexually transmitted diseases worldwide. There currently is no vaccine to protect against chlamydial infection of the female reproductive tract. Vaccine development has predominantly involved using the murine model, however infection of female guinea pigs with Chlamydia caviae more closely resembles chlamydial infection of the human female reproductive tract, and presents a better model to assess potential human chlamydial vaccines. We immunised female guinea pigs intranasally with recombinant major outer membrane protein (r-MOMP) combined with CpG-10109 and cholera toxin adjuvants. Both systemic and mucosal immune responses were elicited in immunised animals. MOMP-specific IgG and IgA were present in the vaginal mucosae, and high levels of MOMP-specific IgG were detected in the serum of immunised animals. Antibodies from the vaginal mucosae were also shown to be capable of neutralising C. caviae in vitro. Following immunisation, animals were challenged intravaginally with a live C. caviae infection of 102 inclusion forming units. We observed a decrease in duration of infection and a significant (p<0.025) reduction in infection load in r-MOMP immunised animals, compared to animals immunised with adjuvant only. Importantly, we also observed a marked reduction in upper reproductive tract (URT) pathology in r-MOMP immunised animals. Intranasal immunisation of female guinea pigs with r-MOMP was able to provide partial protection against C. caviae infection, not only by reducing chlamydial burden but also URT pathology. This data demonstrates the value of using the guinea pig model to evaluate potential chlamydial vaccines for protection against infection and disease pathology caused by C. trachomatis in the female reproductive tract.

Fast rates for estimation error and oracle inequalities for model section

We consider complexity penalization methods for model selection. These methods aim to choose a model to optimally trade off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is well known that if we use a bound on the maximal deviation between empirical and true risks as a complexity penalty, then the risk of our choice is no more than the approximation error plus twice the complexity penalty. There are many cases, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the difference between the risk of the empirical risk minimizer and the minimal risk in the class) approaches zero at a faster rate than the maximal deviation between empirical and true risks. In this paper, we address the question of whether it is possible to design a complexity penalized model selection method for these situations. We show that, provided the sequence of models is ordered by inclusion, in these cases we can use tight upper bounds on estimation error as a complexity penalty. Surprisingly, this is the case even in situations when the difference between the empirical risk and true risk (and indeed the error of any estimate of the approximation error) decreases much more slowly than the complexity penalty. We give an oracle inequality showing that the resulting model selection method chooses a function with risk no more than the approximation error plus a constant times the complexity penalty.

A systematic approach to evaluate the process improvement in lean manufacturing organizations

Numerous tools and techniques have been developed to eliminate or reduce waste and carry out Lean concepts in the manufacturing environment. However, in practice, manufacturers encounter difficulties to clearly identify the weaknesses of the existing processes in order to address them by implementing Lean tools. Moreover, selection and implementation of appropriate Lean strategies to address the problems identified is a challenging task. According best of authors‟ knowledge, there is no method available to quantitatively evaluate the cost and benefits of implementing a Lean strategy to address the weaknesses in the manufacturing process. Therefore, benefits of Lean approaches cannot be clearly established. The authors developed a methodology to quantitatively measure the performances of a manufacturing system in detecting the causes of inefficiencies and to select appropriate Lean strategies to address the problems identified. The proposed methodology demonstrates that the Lean strategies should be implemented based on the contexts of the organization and identified problem in order to achieve maximum cost benefits. Finally, a case study has been presented to demonstrate how the procedure developed works in practical situation.

Co-constructing self-efficacy narratives : a study of four mature age university students

This thesis reports on a study in which research participants, four mature aged females starting an undergraduate degree at a regional Australian university, collaborated with the researcher in co-constructing a self-efficacy narrative. For the purpose of the study, self-efficacy was conceptualized as a means by which an individual initiates action to engage in a task or set of tasks, applies effort to perform the task or set of tasks, and persists in the face of obstacles encountered in order to achieve successful completion of the task or set of tasks. Qualitative interviews were conducted with the participants, initially investigating their respective life histories for an understanding of how they made the decision to embark on their respective academic program. Additional data were generated from a written exercise, prompting participants to furnish specific examples of self-efficacy. These data were incorporated into the individual's self-efficacy narrative, produced as the outcome of the "narrative analysis". Another aspect of the study entailed "analysis of narrative" in which analytic procedures were used to identify themes common to the self-efficacy narratives. Five main themes were identified: (a) participants' experience of schooling . for several participants their formative experience of school was not always positive, and yet their narratives demonstrated their agency in persevering and taking on university-level studies as mature aged persons; (b) recognition of family as an early influence . these influences were described as being both positive, in the sense of being supportive and encouraging, as well as posing obstacles that participants had to overcome in order to pursue their goals; (c) availability of supportive persons – the support of particular persons was acknowledged as a factor that enabled participants to persist in their respective endeavours; (d) luck or chance factors were recognised as placing participants at the right place at the right time, from which circumstances they applied considerable effort in order to convert the opportunity into a successful outcome; and (e) self-efficacy was identified as a major theme found in the narratives. The study included an evaluation of the research process by participants. A number of themes were identified in respect of the manner in which the research process was experienced as a helpful process. Participants commented that: (a) the research process was helpful in clarifying their respective career goals; (b) they appreciated opportunities provided by the research process to view their life from a different perspective and to better understand what motivated them, and what their preferred learning styles were; (c) their past successes in a range of different spheres were made more evident to them as they were guided in self-reflection, and their self-efficacious behaviour was affirmed; and (d) the opportunities provided by their participation in the research process to identify strengths of which they had not been consciously aware, to find confirmation of strengths they knew they possessed, and in some instances to rectify misconceptions they had held about aspects of their personality. The study made three important contributions to knowledge. Firstly, it provided a detailed explication of a qualitative narrative method in exploring self-efficacy, with the potential for application to other issues in educational, counselling and psychotherapy research. Secondly, it consolidated and illustrated social cognitive theory by proposing a dynamic model of self-efficacy, drawing on constructivist and interpretivist paradigms and extending extant theory and models. Finally, the study made a contribution to the debate concerning the nexus of qualitative research and counselling by providing guidelines for ethical practice in both endeavours for the practitioner-researcher.

Practical stability with respect to model mismatch of approximate discrete-time output feedback control

This paper establishes a practical stability result for discrete-time output feedback control involving mismatch between the exact system to be stabilised and the approximating system used to design the controller. The practical stability is in the sense of an asymptotic bound on the amount of error bias introduced by the model approximation, and is established using local consistency properties of the systems. Importantly, the practical stability established here does not require the approximating system to be of the same model type as the exact system. Examples are presented to illustrate the nature of our practical stability result.