A novel Island Model based on Coral Reefs Optimization algorithm for solving the unequal area facility layout problem

This paper proposes a novel approach to address the Unequal Area Facility Layout Problem (UA-FLP), based on the combination of both an Island Model and a Coral Reefs Optimization (CRO) algorithm. Two different versions of this Island Model based on Coral Reefs Optimization Algorithm (IMCRO) are proposed and applied to the UA-FLP. The structure of flexible bays has been selected as effective encoding to represent the facility layouts within the algorithm. The two versions of the proposed approach have been tested in 22 UA-FLP cases, considering small, medium and large size categories. The empirical results obtained are compared with previous state of the art algorithms, in order to show the performance of the IMCRO. From this comparison, it can be extracted that both versions of the proposed IMCRO algorithm show an excellent performance, accurately solving the UA-FLP instances in all the size categories

Semantic-Based Process Mining Technique for Annotation and Modelling of Domain Processes

Semantic technologies aim to represent information or models in formatsthat are not just machine-readable but also machine-understandable. To this effect, thispaper shows how the semantic concepts can be layered on top of the derived models toprovide a more contextual analysis of the models through the conceptualization method.Technically, the method involves augmentation of informative value of the resulting mod-els by semantically annotating the process elements with concepts that they represent inreal-time settings, and then linking them to an ontology in order to allow for a moreabstract analysis of the extracted logs or models. The work illustrates the method usingthe case study of a learning process domain. Consequently, the results show that a systemwhich is formally encoded with semantic labelling (annotation), semantic representation(ontology) and semantic reasoning (reasoner) has the capacity to lift the process miningand analysis from the syntactic to a more conceptual level

Cloud Robotics for Industry 4.0 - A Literature Review

Robots in the industry have been used for decades, much before the so-called Fourth Industrial Revolution. They have been incorporated into industrial processes in various ways, for example, with mechanic arms, in assembly processes, welding, and painting, among others. Industrial robots are located in restricted access sites and their space is delimited by means of physical barriers and security measures. In recent years, Industry 4.0 proposes the use robots, able to collaborate with persons, known as collaborative robots or “cobots”. Cobots are characterized by cooperating with human work, sharing the same workspace, and able to respond to simple human-machine interactions. In addition, given the benefits of applying cloud computing in Industry 4.0, research has been conducted in applying such technologies to robots. The approach is known as “cloud robotics” and appears as an emerging topic. The objective of this work is to carry out a systematic literature review of cloud robotics for Industry 4.0, in an attempt to present the state of the art in this field and identify opportunities for future research. From the analysis of the results, we observe an emerging interest in this area, and we identify main technologies applied, research themes, and application areas, as well as a special interest on security and safety aspects.Part of the Communications in Computer and Information Science book series (CCIS, vol. 1291)Facultad de Informátic

Industry 4.0: an analysis of the impact upon UK-based automotive manufacturing organisations

Industry 4.0 is an emerging technology-based phenomenon that some have described as a new era in manufacturing, which is so potentially disruptive it has sometimes been labelled the fourth industrial revolution. It is argued that since the launch of Industry 4.0 in 2011 (Kagermann et al., 2013) there has been a distinct level of media hype, uncertainty and scepticism surrounding this high technology strategy. Given these uncertainties, this thesis aims to explore the level of Knowledge, Adoption and Impact within the UK automotive and manufacturing industry. Being that Industry 4.0 is still arguably emerging, it was decided that questionnaire surveys and interviews were the most appropriate instruments to provide the flexibility to answer the research questions. It was found from both the interviews and the survey that the overall level of diffusion of Industry 4.0 within the UK automotive manufacturing sector is only beginning to emerge slowly. Despite over 10 years in the making since its launch in Germany in 2011 (Kagermann et al., 2013), the level of awareness remains surprisingly low within the UK automotive manufacturing industry. It was revealed that some within the automotive and manufacturing industry still fail to distinguish between Industry 4.0 and today’s evolving industrial technologies, suggesting a level of confusion persisting within the sector. In contrast, a small number of pioneers were found to have a more thorough understanding of Industry 4.0 and having taken positive steps to engage with this industrial phenomenon, looked to have pushed the boundaries further. With Industry 4.0 beginning to emerge in the UK, confusion has arisen within the automotive manufacturing sector entailing that the level of impact was somewhat difficult to determine. It was observed from the interviews that the push for Industry 4.0 has attracted the attention of many technology providers in their attempt to sell technology and services. The research concluded that despite the ‘revolutionary’ jargon used as marketing hype by these organisations, for the moment Industry 4.0 within the UK automotive manufacturing sector is more around evolution than revolution