Bioprocess development today is slow and expensive compared to chemical process development. A drastic paradigm shift is necessary and possible by the consistent application of engineering strategies ...that are typically used in the process development phase already in the early product development. Aside from providing a consistent pathway, strategies such as statistical‐based design of experiments, fed‐batch, minibioreactors, new on‐line sensors, process modeling, and control tools in combination with automation of manual steps offer a higher success rate and the opportunity to find the optimum parameters and operation point. This also directly benefits the early phases of biomolecular screening and initial production of small amounts of the target molecule. The paper reviews the bioprocess developmental phases from a business perspective and the available systems and technologies.
Traditional methods of analyzing data from psychological experiments are based on the assumption that there is a single random factor (normally participants) to which generalization is sought. ...However, many studies involve at least two random factors (e.g., participants and the targets to which they respond, such as words, pictures, or individuals). The application of traditional analytic methods to the data from such studies can result in serious bias in testing experimental effects. In this review, we develop a comprehensive typology of designs involving two random factors, which may be either crossed or nested, and one fixed factor, condition. We present appropriate linear mixed models for all designs and develop effect size measures. We provide the tools for power estimation for all designs. We then discuss issues of design choice, highlighting power and feasibility considerations. Our goal is to encourage appropriate analytic methods that produce replicable results for studies involving new samples of both participants and targets.
We propose a class of subspace ascent methods for computing optimal approximate designs that covers existing algorithms as well as new and more efficient ones. Within this class of methods, we ...construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to that of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality, which also has applications beyond experimental design, such as the construction of the minimum-volume ellipsoid containing a given set of data points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality, which enable one to use REX and some other algorithms for computing A-optimal and I-optimal designs.
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•We analyzed the main design of experiments (DOE) and their applications in building physics.•We compared how 31 different DOE characterized the thermal performance of a double skin ...facade.•Some designs allowed a good characterization (e.g., CCD and some Taguchi arrays) while others failed.•The extent of the nonlinearity played a crucial role in selecting the optimal design(s).•We developed a general set of guidelines for selecting the optimal DOE.
Although a general set of guidelines and procedures for performing the design of experiments (DOE) exists, the literature lacks a recommended course of action for finding and selecting the optimal design of experiments among a large range of possible designs. This research tries to fill this gap by comprehensively testing more than thirty different DOEs through nearly half a million simulated experimental runs. The performance of various DOEs in the characterization of the thermal behaviour of a double skin façade (DSF) is assessed by comparing the outcomes of the different designs and using the full factorial design (FFD) as the ground truth. Besides the finding for the specific case study used in this investigation, this research allowed us to obtain some broad conclusions on the behaviour of different DOEs, which are summarized and translated into recommendations and a general decision tree chart for selecting the suitable DOE(s). The outcomes of this study help researchers and designers to apply DOEs that consider the extent of nonlinearity and interaction of factors in the investigated process in order to select the most successful and the most efficient designs for the specific process characterization.
•We survey regression and Kriging models and their experimental designs in simulation.•We focus on specific properties and challenges of simulation experiments.•Optimization including robust ...optimization, may use low-order polynomials or Kriging.•Sequential bifurcation provides efficient and effective factor screening.
This article reviews the design and analysis of simulation experiments. It focusses on analysis via two types of metamodel (surrogate. emulator); namely, low-order polynomial regression, and Kriging (or Gaussian process). The metamodel type determines the design of the simulation experiment, which determines the input combinations of the simulation model. For example, a first-order polynomial regression metamodel should use a “resolution-III”design, whereas Kriging may use “Latin hypercube sampling”. More generally, polynomials of first or second order may use resolution III, IV, V, or “central composite” designs. Before applying either regression or Kriging metamodeling, the many inputs of a realistic simulation model can be screened via “sequential bifurcation”. Optimization of the simulated system may use either a sequence of low-order polynomials—known as “response surface methodology” (RSM)—or Kriging models fitted through sequential designs—including “efficient global optimization” (EGO). Finally, “robust”optimization accounts for uncertainty in some simulation inputs.
•Honesty can be considered an important norm in any given society.•However, the lack of generally-accepted games confounds our understanding.•This paper reviews 63 economic and psychological ...experiments into honesty.•The review compares and contrasts experimental design, treatments, and findings.•Monitoring and intrinsic lying costs mitigate dishonest behavior.
Honesty toward strangers can be considered an important norm of any given society. However, despite burgeoning interest in honesty among experimenters, the heterogeneous nature of prior experimental designs obfuscates our understanding of this important topic. The present review of 63 economic and psychological experiments constitutes the first attempt to compare findings across a range of honesty experiments. Our findings across experimental designs suggest the robust presence of unconditional cheaters and non-cheaters, with the honesty of the remaining individuals being particularly susceptible to monitoring and intrinsic lying costs.
The tools and technique used in the Design of Experiments (DOE) have been proved successful in meeting the challenge of continuous improvement over the last 15 years. However, research has shown that ...applications of these techniques in small and medium-sized manufacturing companies are limited due to a lack of statistical knowledge required for their effective implementation. Although many books have been written in this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers.Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as by those using statistical methods and readers will find the concepts in this book both familiar and easy to understand. The book treats Planning, Communication, Engineering, Teamwork and Statistical Skills in separate chapters and then combines these skills through the use of many industrial case studies. Design of Experiments forms part of the suite of tools used in Six Sigma.Key features:* Provides essential DOE techniques for process improvement initiatives* Introduces simple graphical techniques as an alternative to advanced statistical methods - reducing time taken to design and develop prototypes, reducing time to reach the market* Case studies place DOE techniques in the context of different industry sectors* An excellent resource for the Six Sigma training programThis book will be useful to engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic.Dr Jiju Anthony is Senior Teaching Fellow at the International Manufacturing Unit at Warwick University. He is also a trainer and consultant in DOE and has worked as such for a number of companies including Motorola, Vickers, Procter and Gamble, Nokia, Bosch and a large number of SMEs.
We formalize the optimal design of experiments when there is interference between units, that is, an individual’s outcome depends on the outcomes of others in her group. We focus on randomized ...saturation designs, two-stage experiments that first randomize treatment saturation of a group, then individual treatment assignment. We map the potential outcomes framework with partial interference to a regression model with clustered errors, calculate standard errors of randomized saturation designs, and derive analytical insights about the optimal design. We show that the power to detect average treatment effects declines precisely with the ability to identify novel treatment and spillover effects.
Abstract
The search for a dark photon holds considerable interest in the physics community. Such a force carrier would begin to illuminate the dark sector. Many experiments have searched for such a ...particle, but so far it has proven elusive. In recent years the concept of a low mass dark photon has gained popularity in the physics community. Of particular recent interest is the
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Be and
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He anomaly, which could be explained by a new fifth force carrier with a mass of 17 MeV/
c
2
. The proposed Darklight experiment would search for this potential low mass force carrier at ARIEL in the 10-20 MeV/
c
2
e
+
e
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invariant mass range. This proceeding will focus on the experimental design and physics case of the Darklight experiment.
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