Deep Probabilistic Learning for Process Quality Evaluation with a Case Study of Gear Hobbing Process

AbstractThe implementation of agile frameworks, such as SAFe, in large companies causes conflicts between the overall product development process with a rigid linkage to the calendar cycles and the continuous agile project planning. To resolve these conflicts, adaptive processes can be used to support the creation of realistic target-processes, i.e. project plans, while stabilizing process quality and simplifying process management. This enables the usage of standardisation methods and module sets for design processes.The objective of this contribution is to support project managers to create realistic target-processes through the usage of target-process module sets. These target-process module sets also aim to stabilize process quality and to simplify process management. This contribution provides an approach for the development and application of target-process module sets, in accordance to previously gathered requirements and evaluates the approach within a case study with project managers at AUDI AG (N=21) and an interview study with process authors (N=4) from three different companies.

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An intelligent approach for reservoir quality evaluation in tight sandstone reservoir using gradient boosting decision tree algorithm - A case study of the Yanchang Formation, mid-eastern Ordos Basin, China

Marine and Petroleum Geology ◽

10.1016/j.marpetgeo.2021.104939 ◽

2021 ◽

Vol 126 ◽

pp. 104939

Author(s):

Jing-Jing Liu ◽

Jian-Chao Liu

Keyword(s):

Quality Evaluation ◽

Ordos Basin ◽

Gradient Boosting ◽

Reservoir Quality ◽

Decision Tree Algorithm ◽

Tight Sandstone ◽

Yanchang Formation ◽

Sandstone Reservoir ◽

Intelligent Approach

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Planning a holistic summative eHealth evaluation in an interdisciplinary and multi-national setting: a case study and propositions for guideline development

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-021-01399-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Monika Jurkeviciute ◽

Amia Enam ◽

Johanna Torres-Bonilla ◽

Henrik Eriksson

Keyword(s):

Pattern Matching ◽

Quality Evaluation ◽

Empirical Process ◽

Guideline Development ◽

Evaluation Process ◽

Feasibility Analysis ◽

National Team ◽

Matching Technique ◽

Interdisciplinary Setting

Abstract Background Summative eHealth evaluations frequently lack quality, which affects the generalizability of the evidence, and its use in practice and further research. To guarantee quality, a number of activities are recommended in the guidelines for evaluation planning. This study aimed to examine a case of an eHealth evaluation planning in a multi-national and interdisciplinary setting and to provide recommendations for eHealth evaluation planning guidelines. Methods An empirical eHealth evaluation process was developed through a case study. The empirical process was compared with selected guidelines for eHealth evaluation planning using a pattern-matching technique. Results Planning in the interdisciplinary and multi-national team demanded extensive negotiation and alignment to support the future use of the evidence created. The evaluation planning guidelines did not provide specific strategies for different set-ups of the evaluation teams. Further, they did not address important aspects of quality evaluation, such as feasibility analysis of the outcome measures and data collection, monitoring of data quality, and consideration of the methods and measures employed in similar evaluations. Conclusions Activities to prevent quality problems need to be incorporated in the guidelines for evaluation planning. Additionally, evaluators could benefit from guidance in evaluation planning related to the different set-ups of the evaluation teams.

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