Can a House Without a Foundation Support Design?

Author(s):  
Andrew Olewnik ◽  
Kemper Lewis

The House of Quality is a popular tool that supports information processing and decision making in the engineering design process. While its application is an aid in conceptual aspects of the design process, its use as a quantitative decision support tool in engineering design is potentially flawed. This flaw is a result of assumptions behind the methodology of the House of Quality and is viewed as an important deficiency that can lead to potentially invalid and poor decisions. In this paper this deficiency and its implications are explored both experimentally and empirically. The resulting conclusions are important to future use and improvement of the House of Quality as an engineering design tool.

Author(s):  
Jeff Patrick ◽  
Larry A. Stauffer

Abstract We present a decision-support tool that will assist engineers with the design of thermoplastic parts for improved dimensional stability. The tool addresses performance issues that cause significant deformation of the plastic part during its life cycle and thus changes in critical dimensions. The degradation of dimensional stability has a direct influence on the quality of the part and its cost is estimated by applying the Taguchi Loss Function. In this way, the quality cost can be combined with the manufactured cost of the part for a total part cost. The tool helps estimate these manufacturing and quality costs early in the product-development process where changes can be made relatively easily. In this paper we present the design analysis process of the tool, a description of the software, and a case study of its use in an industrial application.


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Natasha Michael ◽  
Clare O’Callaghan ◽  
Ekavi Georgousopoulou ◽  
Adelaide Melia ◽  
Merlina Sulistio ◽  
...  

Abstract Background Views on advance care planning (ACP) has shifted from a focus solely on treatment decisions at the end-of-life and medically orientated advanced directives to encouraging conversations on personal values and life goals, patient-caregiver communication and decision making, and family preparation. This study will evaluate the potential utility of a video decision support tool (VDST) that models values-based ACP discussions between cancer patients and their nominated caregivers to enable patients and families to achieve shared-decisions when completing ACP’s. Methods This open-label, parallel-arm, phase II randomised control trial will recruit cancer patient-caregiver dyads across a large health network. Previously used written vignettes will be converted to video vignettes using the recommended methodology. Participants will be ≥18 years and be able to complete questionnaires. Dyads will be randomised in a 1:1 ratio to a usual care (UC) or VDST group. The VDST group will watch a video of several patient-caregiver dyads communicating personal values across different cancer trajectory stages and will receive verbal and written ACP information. The UC group will receive verbal and written ACP information. Patient and caregiver data will be collected individually via an anonymous questionnaire developed for the study, pre and post the UC and VDST intervention. Our primary outcome will be ACP completion rates. Secondarily, we will compare patient-caregiver (i) attitudes towards ACP, (ii) congruence in communication, and (iii) preparation for decision-making. Conclusion We need to continue to explore innovative ways to engage cancer patients in ACP. This study will be the first VDST study to attempt to integrate values-based conversations into an ACP intervention. This pilot study’s findings will assist with further refinement of the VDST and planning for a future multisite study. Trial registration Australian New Zealand Clinical Trials Registry No: ACTRN12620001035910. Registered 12 October 2020. Retrospectively registered.


Author(s):  
Dawn M. Magnusson ◽  
Irena Shwayder ◽  
Natalie J. Murphy ◽  
Lindsay Ollerenshaw ◽  
Michele Ebendick ◽  
...  

Purpose Despite increasing standardization of developmental screening and referral processes, significant early intervention service disparities exist. The aims of this article are to: (a) describe methods used to develop a decision support tool for caregivers of children with developmental concerns, (b) summarize key aspects of the tool, and (c) share preliminary results regarding the tool's acceptability and usability among key stakeholders. Method Content and design of the decision support tool was guided by a systematic process outlined by the International Patient Decision Aid Standards (IPDAS) Collaborative. Three focus group interviews were conducted with caregivers ( n = 7), early childhood professionals ( n = 28), and a mix of caregivers and professionals ( N = 20) to assess caregiver decisional needs. In accordance with the IPDAS, a prototype of the decision support tool was iteratively cocreated by a subset of caregivers ( n = 7) and early child health professionals ( n = 5). Results The decision support tool leverages images and plain language text to guide caregivers and professionals along key steps of the early identification to service use pathway. Participants identified four themes central to shared decision making: trust, cultural humility and respect, strength-based conversations, and information-sharing. End-users found the tool to be acceptable and useful. Conclusions The decision support tool described offers an individualized approach for exploring beliefs about child development and developmental delay, considering service options within the context of the family's values, priorities, and preferences, and outlining next steps. Additional research regarding the tool's effectiveness in optimizing shared decision-making and reducing service use disparities is warranted.


2019 ◽  
Vol 109 (03) ◽  
pp. 134-139
Author(s):  
P. Burggräf ◽  
J. Wagner ◽  
M. Dannapfel ◽  
K. Müller ◽  
B. Koke

Der wachsende Bedarf an Wandlungsfähigkeit führt zu einer höheren Frequenz in der Umplanung von Montagesystemen und erfordert eine kontinuierliche Überprüfung und Anpassung des Automatisierungsgrades. Um auch die komplexen Umgebungsbedingungen abzubilden, sollen nicht-monetäre Faktoren in den Entscheidungsprozess eingebunden werden. Um die Entscheidung zu unterstützen, stellt dieser Beitrag ein Tool zur Identifizierung und Bewertung von Automatisierungsszenarien mittels einer Nutzwert-Aufwand-Analyse vor.   The increasing need for adaptability in assembly leads to a higher planning frequency of the system and requires continuous checks and adaptations of the appropriate level of automation. To account for the complex environmental conditions, non-monetary factors are included in the decision-making process. This paper presents a decision support tool to identify and evaluate automation scenarios by means of cost and benefit evaluation.


Author(s):  
Jayde King ◽  
John Kleber ◽  
Ashlee Harris ◽  
Barbara Chaparro ◽  
Beth Blickensderfer

General Aviation flight operations have been negatively affected by the slow decreasing weather related accident rate for the last 20 years. Upon further investigation, research suggests, that poor preflight planning and a lack of aviation weather experience and knowledge may be contributing factors to the stagnant weather related accident rate. Our team developed a Preflight Weather Decision Support Tool (PWDST) to help novice pilots access, interpret, and apply weather information. We used a user-centered design process which involved an initial task analysis, low-fidelity prototyping, low-fidelity usability testing, user interviews and expert review. This study assessed and compared the perceived usability, difficulty, and the system assistance satisfaction of the PWDST. Participants (n=9) completed a usability study and a series of surveys during, as well as, after the completion of the preflight planning scenario. A series of Mann-Whitney U Tests were conducted to compare the difference between Private Pilot and Certified Flight Instructors (CFI) perceived usability, difficulty, and system assistance satisfaction ratings. Results indicated, there were no significant differences between group ratings. Overall, both groups reported above average usability, system assistance and low difficulty rating for the PWDST. Future research and possible implications are discussed.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.


2010 ◽  
Vol 97-101 ◽  
pp. 3341-3344
Author(s):  
Dong Bo Wang ◽  
Xiu Tian Yan ◽  
Ning Sheng Guo ◽  
Tao Li

In order to support the dynamic and creative Engineering Design Process (EDP) comprehensively, after a detailed literature review, a multi autonomic objects (AO) flexible workflow is applied into the supporting and management of EDP, its support for decision making, EDP evolution and design activity granularity is explained, finally and most importantly, a genetic algorithm-based AO knowledge learning method is proposed, the algorithm is demonstrated by a MATLAB simulation that it can satisfy the knowledge acquisition in EDP satisfactorily.


Sign in / Sign up

Export Citation Format

Share Document