Big data and Cyber Physical System enabled sustainable project scheduling problems.

Big Data and CPS in Project Scheduling

In the presence of increasingly dynamic environments, frequent uncertainties, high customer specifications, strict project deadlines, and stricter requirements on sustainability and scarcity of resources, modern project managers are challenged in their ability to schedule and control projects. Thus, in the context of sustainable project scheduling context, two important elements are to be considered as decision variables: the input elements of a scheduling (e.g. resources: workforce, machine, money) that enable the realization of a schedule for a project and the output element that are consequences of the realization of the project (e.g. noise, pollution, waste).

In this context, innovative approaches and concepts available in the era of fourth generation industrial revolution, such as cyber-physical systems and big data, can bring insights to the development of effective and efficient sustainable project scheduling systems. Therefore, this project intends to present novel Cyber Physical System (CPS) and Big Data-enabled project scheduling approaches to address the above challenge by ensuring project efficiency and sustainability with regards to the environmental and economic dimensions.

Research objectives

  • A mathematical model of the problem under study will be developed considering both profit-driven objectives (like makespan, profit) and sustainability (like energy consumptions) and temporal constraints.
  • The energy model, which is enabled by CPS, Big Data analytics and intelligent learning algorithms, consider the dynamic conditions of a project
  • A novel scheduling, process monitoring (learning), and rescheduling approach will be designed to enhance projects’ performances.
  • Practical case studies will testify the effectiveness and great potential of applicability of the system in practice.
Funding: 

Ph.D. scholarships ($35,000 per year) are available for high-achieving students (with H1/High Distinction in UG and/or Masters by Research) in engineering, mathematics or relevant sciences under my supervision. 

Supervisor: 
Dr Ripon Chakrabortty
Associate Professor Mike Ryan
Contact: 

Contact Dr. Ripon Chakrabortty (r.chakrabortty@adfa.edu.au) or Dr. Humyun Fuad Rahman (md.rahman@unsw.edu.au) for further information. Each potential student needs to write a research proposal highlighting research motivation, research problems, research objectives, a brief review of the most relevant literature, proposed methodology and expected outcome.