- When? Friday September 1st 14-16
- Where? Onsite: D1172 at Linnaeus University in Växjö and online
- Registration: Please sign up for the PhD-seminar via this link https://forms.gle/PENhmNcQVBRx8ipR9 by August 30th (especially important if you plan on attending onsite so we have fika for everyone)
14.00-14.10 Welcome and practical information from Welf Löwe
14.10-14.55 Presentation and discussion: Digitalization of Work Instructions Gaurav Garg, Industry PhD-student Virtual Manufacturing
14.55 – 15.05 Coffee break
15.05 – 15.50 Presentation and discussion – Towards Smarter Organization; Digital Twin of the Organization Approach – Farid Edrisi, PhD student at LNU
15.50 -16.00 Sum up and plan for our next seminar on October 6th
Towards Smarter Organization; Digital Twin of the Organization Approach – Farid Edrisi, PhD student at LNU
To survive and remain competitive in today’s dynamic, uncertain, and constantly changing environment, organizations must alter their traditional business software solution and be smarter. A smarter organization needs smarter machinery systems. In this context, the smartness of a system could be categorized into 4 levels according to its run-time adaptation level. In this presentation, I will elaborate on the role of Self-Adaptive Systems (SAS) in realizing different levels of a system’s smartness. Although various wave of research on engineering SAS paves the way toward smarter systems, several issues like changing adaptation goals at run time, keeping run time models up-to-date, complex nature of uncertainty and etc. have remained open, yet. To overcome these issues, our solution, which is adding a digital twin as an additional specialized component to modify the managing system of SAS over time, will be introduced along with a robotic example.
While smarter systems mainly contribute to efficiency and effectiveness, becoming a smarter organization requires a holistic approach that considers machinery systems, processes, people, culture, and strategy. Therefore, developing methodologies to facilitate managing, controlling, and evolving the organization as well as dealing with its complexity is crucial. Digital Twin of the Organization (DTO) provides a suitable basis for continuous assessment, optimization, and prediction by representing all the organizational system elements and connections in virtual models and through perpetual simulation and analysis. However, there exist architectural concerns regarding modularity, granularity, decomposition/composition styles, etc., which should be taken into account in developing DTOs. In this presentation, I introduce the EA blueprint pattern with a manufacturing use case to show how DTO can help organizational managers to make informed decisions.