پارس پروژه پرتال خدمات دانشگاهی
این مقاله علمی پژوهشی (ISI) به زبان انگلیسی از نشریه الزویر مربوط به سال ۲۰۲۲ دارای ۱۲ صفحه انگلیسی با فرمت PDF می باشد در ادامه این صفحه لینک دانلود رایگان مقاله انگلیسی و بخشی از ترجمه فارسی مقاله موجود می باشد.
کد محصول: M1263
سال نشر: ۲۰۲۲
نام ناشر (پایگاه داده): الزویر
نام مجله: Expert Systems With Applications
نوع مقاله: علمی پژوهشی (Research articles)
تعداد صفحه انگلیسی: ۱۲ صفحه PDF
عنوان کامل فارسی:
مقاله انگلیسی ۲۰۲۲ : یک رویکرد نمودار تأثیر برای خودکارسازی تخمین زمان تدارک (زمان انتظار) در مدیریت پروژه کانبان چابک
عنوان کامل انگلیسی:
An influence diagram approach to automating lead time estimation in Agile Kanban project management
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Abstract
This research introduces an influence diagram based approach to estimating task lead times for Agile Kanban project management. Derived from the principles of lean manufacturing, Agile methodologies including Scrum, Scrumban, and Kanban are common in the software industry and are spreading to other fields. Many teams estimate task delivery to better manage stakeholder expectations and improve decision making. However, the current technique involves calculating a team’s story point completion velocity, requiring hours of weekly effort while overlooking the addition, removal, and reprioritization of backlog tasks. While these factors may be critical in Scrum, teams practicing Kanban experience these conditions frequently due to the emphasis on continuous integration and reprioritization. Our alternative approach applies an influence diagram, or Bayesian belief network, to model the uncertainties affecting the lead time. To partially automate the estimation process, an influence diagram based expert system is developed and populated with data from a practicing Kanban team and used to generate a cumulative distribution function to facilitate the communication of probabilistic estimates. A sensitivity analysis is conducted to better understand how each factor influences lead times. This system can assist Kanban teams’ stakeholder communication and reduce estimation workload through a more holistic model of lead times.
۱.Introduction
The explainability of decision and prediction-making expert systems has been a topic of research to improve user confidence in automated systems. An understanding of the factors that influence a prediction or recommendation, and the ability to conduct a what-if analysis of multiple scenarios, help a user better understand the system. The depiction of uncertainty in the predictions made by a system further helps the users of the system develop acceptable levels of confidence and reliance in the system. Bayesian theory has been used in expert systems to integrate uncertainty into the system output. A graphical model known as an influence diagram uses this mathematic model to create an explainable model based on Bayes theory and conditional probabilities. This research presents the application of an influence diagram based expert system to depict uncertainty in lead time estimation for Agile Kanban project management. The goal of this study is not to improve the accuracy of the average lead time estimates. Instead, this practical implementation demonstrates the value influence diagrams can bring to an expert system by improving the user and stakeholder understanding of the system and by depicting the associated uncertainties in the system…
۵.Conclusions
The objective of this paper was to provide an alternative approach to lead time estimation for Agile Kanban project teams to account for the addition and removal of tasks to the backlog, their reprioritization, and the team’s level of productivity. This research acts as an example of how influence diagrams can be incorporated into an expert system to make the system more explainable and to communicate uncertainty of the system outputs. Automating this process, through the creation of an expert system, can reduce the level of effort required by the team to produce these estimates. An influence diagram representing the factors impacting the lead time was created and used to create an interactive tool using the software Netica. The probabilistic output of this tool is represented with a CDF graph that can be used by a project team to visually communicate lead time probabilities to stakeholders or to use as a reference during the decision-making process of backlog prioritization…