scholarly journals 84 Students Get Involved: A Novel Approach to Process Improvement Evaluation in Acute Care

2019 ◽  
Vol 74 (4) ◽  
pp. S33
Author(s):  
J. McCready ◽  
D. Albright ◽  
E. Schaller ◽  
L. Salazar ◽  
S. Putnam ◽  
...  
Author(s):  
Richard M. D. Sledd ◽  
Ellen J. Bass ◽  
Stephen M. Borowitz ◽  
Linda A. Waggoner-Fountain

Author(s):  
David Adeniji ◽  
Julius Schoop

Abstract The chief objective of manufacturing process improvement efforts is to significantly minimize process resources such as time, cost, waste, and consumed energy while improving product quality and process productivity. This paper presents a novel physics-informed optimization approach based on artificial intelligence (AI) to generate digital process twins (DPTs). The utility of the DPT approach is demonstrated for the case of finish machining of aerospace components made from gamma titanium aluminide alloy (γ-TiAl). This particular component has been plagued with persistent quality defects, including surface and sub-surface cracks, which adversely affect resource efficiency. Previous process improvement efforts have been restricted to anecdotal post-mortem investigation and empirical modeling, which fail to address the fundamental issue of how and when cracks occur during cutting. In this work, the integration of insitu process characterization with modular physics-based models is presented, and machine learning algorithms are used to create a DPT capable of reducing environmental and energy impacts while significantly increasing yield and profitability. Based on the preliminary results presented here, an improvement in the overall embodied energy efficiency of over 84%, 93% in process queuing time, 2% in scrap cost, and 93% in queuing cost has been realized for γ-TiAl machining using our novel approach.


Author(s):  
David Adeniji ◽  
Julius Schoop

Abstract The chief objective of manufacturing process improvement efforts is to significantly minimize process resources such as time, cost, waste, and consumed energy while improving product quality and process productivity. This paper presents a novel physics-informed optimization approach based on artificial intelligence (AI) to generate digital process twins (DPTs). The utility of the DPT approach is demonstrated for the case of finish machining of aerospace components made from gamma titanium aluminide alloy (γ-TiAl). This particular component has been plagued with persistent quality defects, including surface and sub-surface cracks, which adversely affect resource efficiency. Previous process improvement efforts have been restricted to anecdotal post-mortem investigation and empirical modeling, which fail to address the fundamental issue of how and when cracks occur during cutting. In this work, the integration of in-situ process characterization with modular physics-based models is presented, and machine learning algorithms are used to create a DPT capable of reducing environmental and energy impacts while significantly increasing yield and profitability. Based on the preliminary results presented here, an improvement in the overall embodied energy efficiency of over 84%, 93% in process queuing time, 2% in scrap cost, and 93% in queuing cost has been realized for γ-TiAl machining using our novel approach.


Author(s):  
Richard M. D. Sledd ◽  
Ellen J. Bass ◽  
Stephen M. Borowitz ◽  
Linda A. Waggoner-Fountain

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 211-211
Author(s):  
Paula Reed ◽  
Albert Chan ◽  
Natalia Colocci ◽  
Virginia Carter-West ◽  
Matthew Kunkel ◽  
...  

211 Background: The Palo Alto Medical Foundation (PAMF), an integrated multispecialty physician group and one of five regions of Sutter Health in Northern California, is converting from an electronic chemotherapy ordering and administration system, Intellidose, to Epic Beacon to achieve full EHR integration. As chemotherapy workflows are complex with multiple interactions between providers and high potential for patient harm, we adopted a novel approach of incorporating Lean process improvement principles in advance of our Beacon deployment to improve the design of our software build and increase operational safety and efficiency. Methods: Two multi-disciplinary teams including oncologists, pharmacists, nurses, administrative and technical support staff were deployed; a Sutter Beacon team responsible for technical design and build of the Sutter Beacon standard and a second PAMF team to evaluate workflow variation among PAMF chemotherapy infusion centers, identify best practices, engage the Sutter Beacon Build team around system design and institute rapid cycle process improvement in partnership with the PAMF Lean Promotion Office. Results: Visio maps of current state workflows were constructed to reflect oncologist, pharmacy and nursing workflows from medication ordering to chemotherapy administration and billing submission. Two Rapid Process Improvement Workshops designed future state workflows and identified key areas requiring re-engineering. Lean rapid cycle improvement strategies will be leveraged to improve clinical workflows prior to Beacon implementation. To support the 40% of infusion treatments that are for non-oncology patients, a second process was designed as an important patient safety initiative to avoid discordant nursing administration workflows. Conclusions: Successful design, build and implementation of EHR require achieving consensus-driven work processes that maximize patient safety, eliminate workflow redundancies and maximizes the value-added component. It requires coordination between the EHR technical build team who design the system and the implementation team who integrate it with re-engineered workflows. Lean methodology provides the conceptual framework to achieve a successful EHR deployment.


2019 ◽  
Vol 3 (1) ◽  
pp. 45-61
Author(s):  
Olatunji J Oladiran ◽  
Olabode E Ogunsanmi ◽  
Martin O Dada

A novel approach to solving waste incidence of materials on building projects is to framework the issues and processes that are involved in its minimization. The objective of the study is to develop and validate frameworks for material waste minimization in building projects. This study is a survey research in South West Nigeria. Define, Review, Identify, Verify and Execute (DRIVE) and Construction Process Improvement Methodology (CPIM) techniques were used to develop the proposed frameworks; while the validation was done by face validity and scoring model approaches. A pilot validation was done by five academics while the main validation involved 17 potential end users. Data were analysed with frequency and percentage. The study reveals that the frameworks are clear, informative, appropriate and applicable. It is concluded that the frameworks can minimize material waste at every stage of building projects. It is therefore recommended that the proposed FMWM should be adopted by all stakeholders to prevent and minimize material waste at all stages of building projects.Keywords: CPIM, DRIVE, Frameworks, Minimization, Prevention, Waste.


2010 ◽  
Vol 19 (6) ◽  
pp. e61-e61
Author(s):  
A. M. Yancey ◽  
A. B. Jundt ◽  
K. J. Nelson

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