A comparison of the integration of Risk management Principles in Product Development Approaches

The management and reduction of risk is a central part of product development processes. This paper analyses the extent to which four common product development approaches address risks (waterfall model, stage gate model, design for six sigma, and lean product development). They are analyzed along the four principles of risk-driven design: 1. Identifying and quantifying risks; 2. Making risk-based decisions; 3. Reducing risks; and 4. Creating resilient PD systems. The analysis shows that the existing PD processes only partially address the four principles of risk-driven design and that they have their specific strengths and weaknesses. The paper concludes with a discussion of preliminary empirical findings through interviews and case studies on how to better integrate risk management principles into product development.Massachusetts Institute of Technology. Lean Advancement InitiativeCenter for Clean Water and Clean Energy at MIT and KFUP

Automated Histological Analysis System for Quantifying Microstructural Damage Accumulation to the Annulus Fibrosus

Ben Daya, I., Noguchi, M., Callaghan, J. P., & Wong, A. (2016). Automated Histological Analysis System for Quantifying Microstructural Damage Accumulation to the Annulus Fibrosus. Journal of Computational Vision and Imaging Systems, 2(1). Retrieved from http://openjournals.uwaterloo.ca/index.php/vsl/article/view/100In this paper, we proposed an automated histological analysis system for quantifying microstructural damage accumulation to the annulus fibrosus. This system takes in a digital histology image and uses Gaussian mixture model based segmentation, followed by connected components analysis to extract and label possible clefts. The image is then refined through spatial and size constraints. Finally, the required statistics for quantifying microstructural damage are calculated.This research was funded by the Natural Sciences and Engineering Research Council of Canada, the Canada Research Chairs Program, and the Ontario Ministry of Research and Innovation

Risk Management in Product Design: Current State, Conceptual Model and Future Research

Risk management is an important element of product design. It helps to minimize the project- and product-related risks such as project budget and schedule overrun, or missing product cost and quality targets. Risk management is especially important for complex, international product design projects that involve a high degree of novel technology. This paper reviews the literature on risk management in product design. It examines the newly released international standard ISO 31000 “Risk management — Principles and guidelines” and explores its applicability to product design. The new standard consists of the seven process steps communication and consultation; establishing the context; risk identification; risk analysis; risk evaluation; risk treatment; and monitoring and review. A literature review reveals, among other findings, that the general ISO 31000 process model seems applicable to risk management in product design; the literature addresses different process elements to varying degrees, but none fully according to ISO recommendations; and that the integration of product design risk management with risk management of other disciplines, or between project and portfolio level in product design, is not well developed

Characteristics of successful risk management in product design

The paper reports results of one of the largest empirical studies to-date on the impact of design risk management practices on product design success. Through a survey of 224 practices, 38 (in 7 categories) where found to be statistically significant for at least 3 out of 4 performance metrics. The categories are: 1. Organizational Design Experience; 2. Risk Management Personnel and Resources; 3. Tailoring and Integration of Risk Management Process; 4. Risk-Based Decision Making; 5. Specific Mitigation Actions; 6. Monitoring and Review; and 7. Other ISO Risk Management Principles.King Fahd University of Petroleum and Minerals (Center for Clean Water and Clean Energy at MIT and KFUPM (R11-DMN-09))Massachusetts Institute of Technology. Lean Advancement Initiativ

Characteristics and Enablers of Transparency in Product Development Organizations

Risks in product development lead to schedule and cost overruns and poor product quality. While many risk management frameworks have been published and research on specific practices has been conducted, little is understood of key characteristics of successful risk management in product development and how they manifest in real development projects. This research consists of two phases. The first phase is a survey on 171 best practices in risk management. Analysis of over 200 responses from industry practitioners identified transparency as a key characteristic of successful risk management in product development. Due to the limited exploration of the concept of transparency in the literature, the second phase of this work consisted of a qualitative investigation of transparency through interviews with 15 industry practitioners. Analysis of the interview results suggests a hierarchical structure which decomposes transparency into several characteristics and identifies enablers for each of these characteristics. We propose that transparency can be a valuable lever for product developers and managers. Future work is needed to validate the generalizability of the observations provided

Singularly perturbed nonlinear ODEs and interior point optimizationalgorithms

This paper explores the continuous realizations of iterative processes emanating from interior point optimization algorithms, and their connection with nonlinear singularly-perturbed ordinary differential equations. This mathematical connection provides a theoretical framework for the analysis of the dynamical properties long known and exploited in interior point-based optimization techniques. In addition, this connection is used to show that the logarithmic barrier function is indeed, in some sense, optimu

On Robustness of Deep Neural Networks: A Comprehensive Study on the Effect of Architecture and Weight Initialization to Susceptibility and Transferability of Adversarial Attacks

Neural network models have shown state of the art performance inseveral applications. However it has been observed that they aresusceptible to adversarial attacks: small perturbations to the inputthat fool a network model into mislabelling the input data. Theseattacks can also transfer from one network model to another, whichraises concerns over their applicability, particularly when there areprivacy and security risks involved. In this work, we conduct a studyto analyze the effect of network architectures and weight initial-ization on the robustness of individual network models as well astransferability of adversarial attacks. Experimental results demon-strate that while weight initialization has no affect on the robustnessof a network model, it does have an affect on attack transferabilityto a network model. Results also show that the complexity of anetwork model as indicated by the total number of parameters andMAC number is not indicative of a network’s robustness to attackor transferability, but accuracy can be; within the same architec-ture, higher accuracy usually indicates a more robust network, butacross architectures there is no strong link between accuracy androbustness