The objective of the Center for Digital Supply Chain and Operations Management is to create a faculty cluster with critical mass to conduct high-quality, impactful research and education in three primary thematic areas: digital supply chain, digital operations management, and the future-of-work in a digital enterprise. The thematic focus brings together KU experts in supply chain, data analytics, along with networked systems, to address the extended-enterprises as a nexus of integrated supply-chains, digital-operations management, and market-ready human capital. These areas, with five research projects proposed, are relevant to local and regional needs, and emerging technologies such as Industry 4.0 application and data-analytics driven management. The Center is at the heart of Khalifa University’s research-vertical in “Supply-Chain and Logistics.” The Center also aims to engage purposefully with local industrial and governmental partners and international centers of excellence; some of which the team members have already ongoing research collaborations.
Optimization problems are everywhere, in technology, economy, science, industry, environment, telecommunication, energy, transport, and supply chain management. They occur in private and public sectors, by individual or by small or huge enterprises. Although they are at first glance quite different, fortunately they usually share similar properties. In other words, a variety of problems in different areas of human activities share the similar symbolic presentation or mathematical model. They all have an objective function and the solution space of huge number of solutions, where just one or just a few among them are optimal.
The most useful and the most popular techniques in solving hard real-life optimization problems are so-called heuristic methods that provide approximate or near optimal solutions. Metaheuristics, or frameworks for building heuristic, are trying to establish general principles and rules that should be followed during the search for the better solution. Heuristic approach named ’Less is more approach’ (LIMA) has been recently proposed. Its main idea is to find the minimum number of search ingredients in solving some optimization problem that makes some heuristic more efficient than the currently best in the literature. More precisely, the goal is to make heuristic as simple as possible, but at the same time more effective and efficient than the current state-of-the-art heuristic. Several problems that follow LIMA idea have already been successfully implemented. They include area such as continuous optimization, dispersion, constrained clustering, etc.
In this project, we plan to continue research in LIMA direction and apply it to some new practical important problems:
In the field of Automatic Programming (AP), the solution of a problem is a program, which is usually represented by an AP tree. Application examples are symbolic regression, classification, and prediction that are very often used in engineering, energy planning, supply chains, etc.
The wide adoption of li-ion batteries in electric vehicles, consumer electronics, and energy storage in the last few decades has resulted in huge amounts of retired batteries being routed to landfills or to other recycling centers that may not be equipped with facilities needed to recycle them. The reuse and recycling of end-of-life (EOL) li-ion batteries have become a necessity in many countries around the world, and the United Arab Emirates is not an exception. In fact, those EOL batteries are not allowed to be disposed in landfills because of the adverse environmental effects, which include emissions of toxic gases and possible contamination of surface and ground water. The goal of this project is to develop simple, economic, environment-friendly recycling processes for li-ion batteries using new recycling methods such as direct and mechanical recycling and hydrometallurgy. It is also worth mentioning that end-of-life batteries provide a sources of high-value materials such as cobalt, lithium, and nickel. We also aim to develop techno-economic models to study the dynamics of the supply chain and environmental impacts from production and recycling of li-ion batteries using life cycle assessment approaches.
We propose a novel Blockchain-based supply chain framework that utilizes crowdsourcing and vehicle-to-vehicle (V2V) technologies to optimize the multistage supply chain process by efficiently managing the resources among involved businesses and crowdsourced participants. The platform is in line with Supply Chain 4.0, providing better flexibility in terms of management through ad-hoc and real-time planning. The deployment of Blockchain provides a trusted infrastructure that establishes trust among businesses and ensures secure payment. V2V technology introduces another layer of communication among selected participants to improve the quality of service in the supply chain. Crowdsourcing technologies will be used to efficiently delegate tasks, increase agility, reduce cost, and improve last-mile delivery logistics. The primary outcome of the project is to demonstrate the feasibility of the proposed framework and its performance. Such a framework will motivate and incentivize cooperation among businesses and the crowd to assure traceability, cost-effectiveness, liability, and quality of service.
Blockchain is a disruptive and transformational technology with huge potential, growth, and impact on many industries, businesses, and governments. Locally in the UAE, the Dubai government has mandated that all government-based transactions be paperless and carried out using blockchain by the year 2020. Blockchain is poised to be the preferred technology to solve many challenging problems in healthcare. Moreover, IoT has now become one of the most hyped technologies these days. In this research project, we leverage blockchain and IoT technologies to solve and manage efficiently and in a decentralized, secure, and trusted manner the following three critical problems in healthcare: (i) cold supply chain operations and management applied to sensitive healthcare items such as vaccines, organs, and blood samples; (ii) globally accessible and credible medical history and record of drug administration to ensure patient rights and safety; and (iii) governance of access, control, and sharing of medical IoT (MIoT) devices and their data.
