Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework

Online experimentation in automotive software engineering

Context: Online experimentation has long been the gold standard for evaluating software towards the actual needs and preferences of customers. In the Software-as-a-Service domain, various online experimentation techniques are applied and proven successful. As software is becoming the main differentiator for automotive products, the automotive sector has started to express an interest in adopting online experimentation to strengthen their software development process. Objective: In this research, we aim to systematically address the challenges in adopting online experimentation in the automotive domain.Method: We apply a multidisciplinary approach to this research. To understand the state-of-practise in online experimentation in the industry, we conduct case studies with three manufacturers. We introduce our experimental design and evaluation methods to real vehicles driven by customers at scale. Moreover, we run experiments to quantitatively evaluate experiment design and causal inference models. Results: Four main research outcomes are presented in this thesis. First, we propose an architecture for continuous online experimentation given the limitations experienced in the automotive domain. Second, after identifying an inherent limitation of sample sizes in the automotive domain, we apply and evaluate an experimentation design method. The method allows us to utilise pre-experimental data for generating balanced groups even when sample sizes are limited. Third, we present an alternative approach to randomised experiments and demonstrate the application of Bayesian causal inference in online software evaluation. With the models, we enable software online evaluation without the need for a fully randomised experiment. Finally, we relate the formal assumption in the Bayesian causal models to the implications in practise, and we demonstrate the inference models with cases from the automotive domain. Outlook: In our future work, we plan to explore causal structural and graphical models applied in software engineering, and demonstrate the application of causal discovery in machine learning-based autonomous drive software

The safety case and the lessons learned for the reliability and maintainability case

This paper examine the safety case and the lessons learned for the reliability and maintainability case

The liminality of trajectory shifts in institutional entrepreneurship

In this paper, we develop a process model of trajectory shifts in institutional entrepreneurship. We focus on the liminal periods experienced by institutional entrepreneurs when they, unlike the rest of the organization, recognize limits in the present and seek to shift a familiar past into an unfamiliar and uncertain future. Such periods involve a situation where the new possible future, not yet fully formed, exists side-by-side with established innovation trajectories. Trajectory shifts are moments of truth for institutional entrepreneurs, but little is known about the underlying mechanisms of how entrepreneurs reflectively deal with liminality to conceive and bring forth new innovation trajectories. Our in-depth case study research at CarCorp traces three such mechanisms (reflective dissension, imaginative projection, and eliminatory exploration) and builds the basis for understanding the liminality of trajectory shifts. The paper offers theoretical implications for the institutional entrepreneurship literature

Observing Suppliers observing Early Supplier Involvement: An Empirical Research based upon the Social Systems Theory of Niklas Luhmann.

supplier, involvement, Luhmann

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Inventory simulation and optimization using system dynamics, structural modeling equations and genetic algorithms in the drivetrain division of an automotive manufacturer

Strategic planning and control are among the most critical activities that modern enterprises require to succeed in the global economy. This research is an original study that investigated the combination of tools and methodologies in order to apply them to a midwestern tractor manufacturer. The current study identified the constraints applicable to a polishing line in the Drivetrain Division of a major tractor manufacturer interested in exploring alternative techniques to improve its worldwide manufacturing operations. The specific questions that this project tried to respond are stated as follows: What were the most important variables that affected inventory levels of an assembly line of an automotive manufacturer? What were the significant effects of the causal relationships identified in order to determine an initial model structure? What constrains restrict the behavior and improvement of the selected variables? What levels of the selected variables could be used in order to improve production levels? The current research explored the impact of a series of variables (work-in process, process utilization, cycle time, queue size, utilization of work centers, capacity, and others) in order to examine their impact in the overall performance of the polishing line. Two main models were developed based on two algorithms created for each of the selected part families (PTO and Covers), and in combination determined material flow, resource utilization, and sequencing within and outside the automatic polishing line. The two computer models combined both dynamic and discrete simulation to establish a reference to be used for improvement of similar processes within the company using structural equations modeling, path analysis, scatter plot diagrams, and eigen value plot. Besides, the results of this research indicated that: (a) cycle time can be improved with the addition of a new transporter in order to reduce the moving time within and between work centers; (b) the queue sizes of the polishing line were not improved significantly using either genetic algorithms (GA) and full factorial designs because of the low initial variability of the system; (c) the structural modeling equations model allowed to identify possible material flow errors based on its relationships, in this way it is possible to have a benchmark to compare both the results of the current study and the outcomes of similar studies developed by the company. In summary, a new methodology has been developed in order to study and optimize manufacturing systems, and avoid cost reductions without any statistical significance that might affect the strategic position of the company in the long run. The current study did not give a simple answer to the complexity of the discussed problem, but an alternative to many of the current academic and industrial solutions that can have more than one correct answer

Assessing the Human Factor in Truck Driving

Human factors assessment techniques are commonly applied to a variety of workplaces to examine the nature of operations and how key functions are controlled operationally; however, these tools appear to overlook key aspects of truck driving, particularly the driver’s relationship to the driving experience. The fundamental issue is with the ability to completely decompose truck driving and accurately document the truck drivers working environment will be problematic. Therefore, to demonstrate how a truck driver moves between each series of sub-tasks will require a purpose-built assessment tool that that is both practical and relevant to truck driving

Annual performance indicators of enforced driver behaviours in South Australia, 2007

This report was produced to quantify performance indicators for selected enforced driver behaviours (drink driving, drug driving, speeding and restraint use) in South Australia for the calendar year 2007. The level of random breath testing (RBT) in South Australia in 2007 decreased slightly but remained at a relatively high level. The proportion of tests conducted using mobile RBT continued to increase. The detection rate based on evidentiary testing increased in 2007 to the highest level on record, while the detection rate for screening tests decreased. Detection rates in South Australia were comparable with those in other states. Just over 12,000 drug tests were conducted during 2007, the first full year of random drug testing. Relative to other Australian jurisdictions supplying comparative data, South Australia had the highest testing rate per head of population. Around 24 drivers per 1,000 tested were confirmed positive for at least one of the three prescribed drugs with methylamphetamine the most commonly detected drug. Of the fatally injured drivers who were drug tested in 2007, 25 per cent tested positive for illicit drugs. There was a slight decrease in the number of hours spent on speed detection in 2007. Nevertheless, the total number of speed detections increased, with increases observed for speed camera and red light/speed cameras, the latter most likely due to the expansion of the program. The detection rate (per hour of enforcement and per 1,000 vehicles passing speed cameras) increased by around 30 per cent. Data from systematic speed surveys, introduced in 2007, indicated that travelling speeds on South Australian roads were increasing. The number of restraint offences in 2007 decreased by 14 per cent. Males were charged with more restraint offences and were more likely to be unrestrained in fatal and serious injury crashes than females, indicating that males remain an important target for restraint enforcement. The 2007 publicity campaign focused on the consequences of not using restraints rather than increasing the perceived risk of detection.LN Wundersitz, K Hiranandani, MRJ Baldoc

Risk across design domains

Design processes involve risk: to life and limb if the product is unsafe, to the financial health of the company if the product is late, unsuccessful or simply the wrong product, as well as to the emotions and careers of the designers. Many of the risks are shared universally by all designers, but each different industry and each different project faces its own spectrum of serious and minor risks. Different industries have put their methodological effort into finding ways to mitigate the risks they recognise as important. As part of the Across Design project exploring similarities and differences between design processes in different industries, this paper examines how risks are perceived and handled in different types of design process, and proposes that designers and managers can usefully look to other industries for ways to handle risks that are more central for those other industries