Dr. Savas Konur, ReaderDepartment of Computer Science, University of Bradford, Bradford, UK
Speech Title: Industry 4.0 for Food Manufacturing: A Case Study
Abstract: Industry 4.0 is a transformation of industrial processes by utilising digital and smart technologies. When implemented, it has a huge impact on efficiency, productivity and profitability of businesses. This however requires overcoming a list of challenges. In this talk, we will present the case of a traditional food manufacturer (a typical plant for such type of business), still using the machinery more than one hundred years old, and their move towards the Industry 4.0 technologies. We will report the challenges we have encountered during the transformation process. We will present a novel smart platform that we have developed by utilising a number of emerging technologies, e.g. Internet of Things, Machine Learning, Big Data Analytics, Cyber Physical Systems and Cloud Computing. Our platform, integrated into the company’s existing production facilities, provides a novel data collection, information extraction and intelligent monitoring process, which has led to improving efficiency and consistency and reduction in operational costs. One of the significances of our approach is that the company was not required to replace old machinery outright, but rather adapted the existing machinery to an entirely new way of operating. The proposed approach can benefit similar food manufacturing industries and other industries.
Keywords: Industry 4.0, Smart Manufacturing, Food Manufacturing, Internet of Things, Artificial Intelligence, Machine Learning, Big Data
Biography: Dr Savas Konur is a Reader in Computer Science at University of Bradford. His research interests cover computational and data-driven modelling and analysis, formal verification, machine learning, industrial big data analytics, design and development of software platforms for manufacturing and productions systems as well as systems and synthetic biology. He has published in numerous prestigious journals (e.g. SoftwareX, ACS Syn. Bio., IEEE/ACM Trans. Compt. Bio. & Bioinf., Infor. Sci., Robot. Auto. Sys., Theo. Comp. Sci, Fund. Inf., etc.) as well as many leading conferences (e.g. Int. Conf. on Membr. Comp., Int. Sym. on Formal Meth., Int. Conf. Auto. Reason., IEEE Int. Conf. on High Perfor. Comp., Int. Conf. on Swarm Intel., Int. Symp. in Integ. Bioinf., IEEE Vehic. Tech. Conf., etc.). He has an extensive experience in leading research and industry projects. His research has been funded by EPSRC, Innovate UK, EU and industry. In his recent projects, he has developed intelligent systems utilising advance machine learning and internet of things technologies in manufacturing and engineering systems. His work been rated ‘outstanding’ and awarded the ‘certificate of excellence’ by Innovate UK and has been recently shortlisted by KTN (UK Knowledge Transfer Network) in the Finalist for the Engineering Excellence Category.