Sustainable Production, Analytics and Remanufacturing eXploration
About Us
Our
Vision
To continue to be a leader in Atlantic Canada in Industry 4.0, smart logistics, and sustainable systems research with a focus on prescriptive analysis. To provide an immersive research experience for students by exposing them to high-quality high-impact research. To serve as a hub for university-industry collaboration in Atlantic Canada in sustainable production, manufacturing, and distribution optimization through core prescriptive analytics techniques deterministic, stochastic and robust operations research, data mining/machine learning, simulation-based optimization, life-cycle analysis and system dynamics.
Our
Mission
Conduct research in engineering design of production-distribution systems in the Industry 4.0 and hyperconnected logistics era including reliability and maintenance engineering, green logistics, energy optimization and closed-loop supply chain management.
Equip students and researchers with an advanced technology environment to stimulate high-quality high-impact research in operational research, data mining and machine learning data analytics, and digital twinning.
Raise research funds to support the training of highly qualified personnel (HQP) and purchase of state-of-the-art hardware and software.
Create a truly inclusive, equitable and diverse environment for students, faculty and staff that fosters individual and team growth and celebrates the diverse experiences of its members; promoting excellence in equity, diversity, inclusion, and access (EDIA) by sharing our experiences.
Foster collaboration with other academic units at Dalhousie University in alignment with the missions of the Faculty of Engineering and Dalhousie University in pursuit of UNDP’s Sustainable Production Goals (SPGs).
Reach out to the local community and industry and work with them to turn knowledge into practice, while using this opportunity to provide an immersive experience for all levels of HQP.
Promote collaborate research with individuals and teams with similar interests within the Industrial Engineering and Operational Research community internationally.
