2020
Authors
Soares, R; Marques, A; Gomes, R; Guardão, L; Hernández, E; Rebelo, R;
Publication
Lecture Notes in Mechanical Engineering
Abstract
The potential of the Internet of Things (IoT) and other technologies in the realm of Industry 4.0 to generate valuable data for monitoring the performance of the production processes and the whole supply chain is well established. However, these large volumes of data can be used within planning and control systems (PCSs) to enhance real-time planning and decision-making. This paper conducts a literature review to envisage an overall system architecture that combines IoT and PCS for planning, monitoring and control of operations at the level of an industrial production process or at the level of its supply chain. Despite the extensive literature on IoT implementations, few studies explain the interactions between IoT and the components of PCS. It is expected that, with the increasing digitization of business processes, approaches with PCS and IoT become ubiquitous in the near future. © 2020, Springer Nature Switzerland AG.
2019
Authors
Rivolli, A; Amaral, C; Guardão, L; de Sá, CR; Soares, C;
Publication
Discovery Science - 22nd International Conference, DS 2019, Split, Croatia, October 28-30, 2019, Proceedings
Abstract
Chatbots have been used in business contexts as a new way of communicating with customers. They use natural language to interact with the customers, whether while offering products and services, or in the support of a specific task. In this context, an important and challenging task is to assess the effectiveness of the machine-to-human interaction, according to business’ goals. Although several analytic tools have been proposed to analyze the user interactions with chatbot systems, to the best of our knowledge they do not consider user-defined criteria, focusing on metrics of engagement and retention of the system as a whole. For this reason, we propose the KnowBots tool, which can be used to discover relevant patterns in the dialogues of chatbots, by considering specific business goals. Given the non-trivial structure of dialogues and the possibly large number of conversational records, we combined sequential pattern mining and subgroup discovery techniques to identify patterns of usage. Moreover, a friendly user-interface was developed to present the results and to allow their detailed analysis. Thus, it may serve as an alternative decision support tool for business or any entity that makes use of this type of interactions with their clients. © Springer Nature Switzerland AG 2019.
2021
Authors
Sadeghi, P; Guardão, L; Rebelo, RD; Ferreira, JS;
Publication
Proceedings of the International Conference on Industrial Engineering and Operations Management
Abstract
The paper deals with a relevant scheduling problem associated with moulding injection machines. A footwear company, equipped with advanced automation machinery, faces true difficulties in planning the injection equipment production. It is crucial to respect delivery times without disruptions. There are many conditions associated with footwear and technological issues to consider, such as the weekly demand for different models and sizes, which is major to satisfy them on time. The moulds for each size of a model and distinct available machines, with varying quantities of positions for the moulds, are other concerned matters. Changeover times, which occur when changing moulds, are critical. Stocks are also considered. The time horizon attains tens of weeks. We developed an integer optimisation model with the objectives of minimising both changeovers and stocks. That initial model underwent a few simplifications, acceptable from a strategic and technological point of view, due to the impossibility of reaching admissible solutions. The new version can solve the real dimension problems optimally, those that matter. The paper describes one case, and the solution obtained. The new approach followed, and the solutions obtained, are essential for the company, given the planning difficulties; moreover, the method may also be relevant for any footwear industry facing similar combinatorial optimisation problems. © IEOM Society International.
2024
Authors
Teixeira, J; Guardão, L; Mêda, P; Moreira, J; Sousa, R; Sousa, H; Ribeiro, Y;
Publication
5º Congresso Português de Building Information Modelling Volume 1: ptBIM
Abstract
2023
Authors
Pinto, P; Catorze, C; Guardão, L; Lima, L; Moutinho, J; Dias, JP; Amândio, M; Martins, P; Silva, L; Rodrigues, R;
Publication
CENTERIS 2023 - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2023, Porto, Portugal, November 8-10, 2023.
Abstract
The delivery of concrete is a crucial process in construction projects, and any delay or error can cause significant setbacks and added costs. Thus, effective real-time management of concrete delivery is essential to ensure timely and successful project completion. In this paper, we will discuss a practical and manufacturer-agnostic approach to real-time management of concrete delivery for construction named BET 4.0 that is being conceived with a close partnership with a construction company. This application provides the possibility to optimize the whole concreting process as it establishes the connection between all the relevant components and stakeholders involved in the construction process, namely the concrete plant, the transport, and the construction site, interfacing with all actors involved, and benefiting from real-time data produced by installed sensors in the several components such as machines, plants, or construction elements.
2023
Authors
Pinto, P; Catorze, C; Lima, L; Guardão, L; Moutinho, J; Dias, JP; Amândio, M; Martins, P; Silva, L; Afonso, J; Figueiredo, J;
Publication
CENTERIS 2023 - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2023, Porto, Portugal, November 8-10, 2023.
Abstract
Infrastructure construction companies encounter numerous challenges in managing large and dispersed teams, along with fragmented or non-existent operational data. These challenges often result in delays, inefficiencies, and over-budget projects. Road pavement works are an example of this, as they heavily rely on expensive heavy construction equipment that requires detailed planning and real-time adjustments. Also, pavement quality is closely linked to the quality of the asphalt mixture in terms of viscosity and compactability, which is significantly influenced by temperature. This paper describes the features, challenges and results of a road paving real-time management system that was conceived in a co-creation environment with a construction company. Such a partnership has allowed to specify the requirements of such an application aligned with the identified needs of a real-world development. According with the state-of-the-art, this innovative system is unique in the way it is manufacturer-agnostic and designed to be compatible with most situations. It is also data production-oriented to allow future developments that may provide business analytics or scientific research in the road paving area. This work also presents the development of sensors such as a high precision geolocalized infrared matricial temperature sensor for the application of the bituminous mixture, the data and communication structure, and a web-based interface that manages the construction projects for different stakeholders.
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