Design of experiments for non-manufacturing processes : benefits, challenges and some examples

Design of Experiments (DoE) is a powerful technique for process optimization that has been widely deployed in almost all types of manufacturing processes and is used extensively in product and process design and development. There have not been as many efforts to apply powerful quality improvement techniques such as DoE to improve non-manufacturing processes. Factor levels often involve changing the way people work and so have to be handled carefully. It is even more important to get everyone working as a team. This paper explores the benefits and challenges in the application of DoE in non-manufacturing contexts. The viewpoints regarding the benefits and challenges of DoE in the non-manufacturing arena are gathered from a number of leading academics and practitioners in the field. The paper also makes an attempt to demystify the fact that DoE is not just applicable to manufacturing industries; rather it is equally applicable to non-manufacturing processes within manufacturing companies. The last part of the paper illustrates some case examples showing the power of the technique in non-manufacturing environments

Using Experiments to Foster Innovation and Improve the Effectiveness of Energy Efficiency Programs

This paper argues that the establishment of a process designed to manage innovation must be developed in California to foster the creation of needed program improvements and develop new and more effective energy efficiency delivery programs. This paper discusses several key institutional problems that must be overcome to achieve significant progress

Searching for improvement

Engineering design can be thought of as a search for the best solutions to engineering problems. To perform an effective search, one must distinguish between competing designs and establish a measure of design quality, or fitness. To compare different designs, their features must be adequately described in a well-defined framework, which can mean separating the creative and analytical parts of the design process. By this we mean that a distinction is drawn between coming up with novel design concepts, or architectures, and the process of detailing or refining existing design architecture. In the case of a given design architecture, one can consider the set of all possible designs that could be created by varying its features. If it were possible to measure the fitness of all designs in this set, then one could identify a fitness landscape and search for the best possible solution for this design architecture. In this Chapter, the significance of the interactions between design features in defining the metaphorical fitness landscape is described. This highlights that the efficiency of a search algorithm is inextricably linked to the problem structure (and hence the landscape). Two approaches, namely, Genetic Algorithms (GA) and Robust Engineering Design (RED) are considered in some detail with reference to a case study on improving the design of cardiovascular stents

Improvement Research Carried Out Through Networked Communities: Accelerating Learning about Practices that Support More Productive Student Mindsets

The research on academic mindsets shows significant promise for addressing important problems facing educators. However, the history of educational reform is replete with good ideas for improvement that fail to realize the promises that accompany their introduction. As a field, we are quick to implement new ideas but slow to learn how to execute well on them. If we continue to implement reform as we always have, we will continue to get what we have always gotten. Accelerating the field's capacity to learn in and through practice to improve is one key to transforming the good ideas discussed at the White House meeting into tools, interventions, and professional development initiatives that achieve effectiveness reliably at scale. Toward this end, this paper discusses the function of networked communities engaged in improvement research and illustrates the application of these ideas in promoting greater student success in community colleges. Specifically, this white paper:* Introduces improvement research and networked communities as ideas that we believe can enhance educators' capacities to advance positive change. * Explains why improvement research requires a different kind of measures -- what we call practical measurement -- that are distinct from those commonly used by schools for accountability or by researchers for theory development.* Illustrates through a case study how systematic improvement work to promote student mindsets can be carried out. The case is based on the Carnegie Foundation's effort to address the poor success rates for students in developmental math at community colleges.Specifically, this case details:- How a practical theory and set of practical measures were created to assess the causes of "productive persistence" -- the set of "non-cognitive factors" thought to powerfully affect community college student success. In doing this work, a broad set of potential factors was distilled into a digestible framework that was useful topractitioners working with researchers, and a large set of potential measures was reduced to a practical (3-minute) set of assessments.- How these measures were used by researchers and practitioners for practical purposes -- specifically, to assess changes, predict which students were at-risk for course failure, and set priorities for improvement work.-How we organized researchersto work with practitioners to accelerate field-based experimentation on everyday practices that promote academic mindsets(what we call alpha labs), and how we organized practitioners to work with researchers to test, revise, refine, and iteratively improve their everyday practices (using plando-study-act cycles).While significant progress has already occurred, robust, practical, reliable efforts to improve students' mindsets remains at an early formative stage. We hope the ideas presented here are an instructive starting point for new efforts that might attempt to address other problems facing educators, most notably issues of inequality and underperformance in K-12 settings

Numerical and experimental investigation of a new film cooling geometry with high P/D ratio

In order to improve the coolant surface coverage, in the past years new geometries have been proposed with higher lateral fan-shaped angle and/or greater inter-hole pitch distance (P/D). Unfortunately it is not possible to increase the fan angle or the pitch distance even further without inducing a coolant separation and a drop in the overall effectiveness. This study proposes an innovative design which improves the lateral coverage and reduces the jet lift off. The results have been validated by a combination of numerical and experimental analyses: the experimental work has been assessed on a flat plate using thermo chromic liquid crystals and the results have been confirmed numerically by the CFD with the same conditions. The CFD simulations have been carried out considering a stochastic distribution for the free stream Mach number and the coolant blowing ratio. The experimental and computational results show that the inducing lateral pressure gradients there is a minimum increase in lateral averaged adiabatic effectiveness of +30% than the baseline case until a distance downstream of 20 times the coolant diameter. © 2013 Elsevier Ltd. All rights reserved