İş Akış Motoru Tasarımı ve Gerçekleştirilmesi

Year 2020, , 219 - 231, 24.01.2020

Semih Utku , Oğuzhan Kayış

https://doi.org/10.21205/deufmd.2020226422

Abstract

Bu çalışma özellikle büyük ölçekli
işletmelerin süreçlerinde kullandıkları bir yapı olan iş akışı motorunun
dinamik işleyecek şekilde bir tasarımını ve gerçekleştirilmesini kapsamaktadır.
Üzerinde çalıştığımız temel konu, geliştirdiğimiz sistemin farklı işletmelere
ve işletmeler içerisindeki farklı süreçlere uyum sağlayabilecek esneklikte
olmasıdır. Endüsriyel alanlarda iş süreci bir çok etmene göre zamanla
değişmektedir. Bu amaçla çalışma kapsamında iş akış motoruyla bütünleşik
çalışabilen bir kural motoru geliştirilmiştir. Kural motoru, iş akış motorunun
değişen iş süreçlerine çalışma zamanlı olarak uyum sağlamasını amaçlamaktadır. Tasarlanan
bu sistem, bir teknoloji ürünleri firmasında, ürünlere bağlı belgelerin takip
süreçlerini otomatize etmek üzere uygulanmıştır. Uygulama sonucunda toplanan
bilgiler, sıralı örüntü madenciliği yöntemleri kullanılarak analiz edilmiştir.

Keywords

İş Akış Motoru, Kural Motoru, Sıralı Örüntü Madenciliği

Workflow Engine Design and Implementation

Abstract

This study includes a design and
implementation of a workflow engine which is a structure that is used in the
processes dynamically of the large-scale enterprises. The main issue is creating
a dynamic system that is flexible enough to adapt to different businesses and
different processes within the enterprises. Business process in industrial
areas changes over time according to many factors. For this purpose, within the
scope of the study, a rule engine integrated with the workflow engine was
developed. The rule engine enables the workflow engine to adapt to changing
business processes at runtime. This system was designed to automate the
follow-up processes of the documents connected to the products in a technology
products company.  In addition, the
results of the study were analysed using sequential pattern mining methods.

Keywords

Workflow Engine, Rule Engine, Sequential pattern mining

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