| 1. |
- Gandhi, Kanika, et al.
(författare)
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Towards data mining based decision support in manufacturing maintenance
- 2018
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Ingår i: Procedia CIRP. - : Elsevier. - 2212-8271 .- 2212-8271. ; 72, s. 261-265
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Tidskriftsartikel (refereegranskat)abstract
- The current work presents a decision support system architecture for evaluating the features representing the health status to predict maintenance actions and remaning useful life of component. The evaluation is possible through pattern analysis of past and current measurements of the focused research components. Data mining visualization tools help in creating the most suitable patterns and learning insights from them. Estimations like features split values or measurement frequency of the component is achieved through classification methods in data mining. This paper presents how the quantitative results generated from data mining can be used to support decision making of domain experts.
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| 2. |
- Schmidt, Bernard, 1981-, et al.
(författare)
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Augmented Reality Approach for a User Interface in a Robotic Production System
- 2022
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Ingår i: SPS2022. - Amsterdam; Berlin; Washington, DC : IOS Press. - 9781643682686 - 9781643682693 ; , s. 240-251
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Konferensbidrag (refereegranskat)abstract
- In a Cyber-physical system, the information flow from the cyber part to the physical part plays a crucial role. This paper presents the work of development and initial testing of an augmented reality approach to provide a user interface for operators that could be a part of a robotic production system. The solution is distributed and includes a communication hub that allows the exchange of data and information between multiple clients e.g. robot controllers, an optimization platform, and visualization devices. The main contributions of the presented work are visualization of optimization results and visualization of information obtained from the robot controller and the integrated communication framework. The paper also presents challenges faced during the development work and opportunities related to the presented approach. The implemented interface uses HoloLens 2 mixed reality device to visualize in real-time information obtained from a robot controller as well as from simulation. Information regarding the placement of work objects and targets or currently executed lines of code can be useful for robotic cell programmers and commissioning teams to validate robot programs and to select more optimal solutions toward sustainable manufacturing. The operator can simulate the execution of the robot program and visualize it by overlying the robot cell with the 3D model of the simulated robot. Moreover, visualization of future robot motion could support human-robot collaboration. Furthermore, the interface allows providing the user with details from multi-objective optimization performed on a digital twin of the robotic cell with the aim to reduce cycle time and energy consumption. It allows visualizing selected scenarios to support decision-making by allowing comparison of proposed solutions and the initial one. The visualization includes cell layout, robot path, cycle time, robot energy consumption. The presented approach is demonstrated in industry-inspired cases and with the use of an industrial ABB robot.
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| 3. |
- Schmidt, Bernard, 1981-, et al.
(författare)
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Integration of events and offline measurement data from a population of similar entities for condition monitoring
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In this paper, an approach for integration of data from different sources and from a population of similar monitored entities is presented with evaluation procedure based on multiple machine learning methods that allows selection of a proper combination of methods for data integration and feature selection. It is exemplified on the real-world case from manufacturing industry with application to double ball-bar measurement from a population of machine tools. Historical data from the period of four years from a population of 29 similar multitask machine tools are analysed. Several feature selection methods are evaluated. Finally, simple economic evaluation is presented with application to proposed condition based approach. With assumed parameters, potential improvement in long term of 6 times reduced amount of unplanned stops and 40% reduced cost has been indicated with respect to optimal time based replacement policy.
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| 4. |
- Schmidt, Bernard, 1981-
(författare)
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Toward Predictive Maintenance in a Cloud Manufacturing Environment : A population-wide approach
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The research presented in this thesis is focused on improving industrial maintenance by using better decision support that is based on a wider range of input information. The core objective is to research how to integrate information from a population of similar monitored objects. The data to be aggregated comes from multiple disparate sources including double ball-bar circularity tests, the maintenance management system, and the machine tool’s controller. Various data processing and machine learning methods are applied and evaluated. Finally, an economic evaluation of the proposed approach is presented. The work performed is presented in five appended papers.Paper I presents an investigation of cloud-based predictive maintenance concepts and their potential benefits and challenges.Paper II presents the results of an investigation of available and potentially useful data from the perspective of predictive analytics with a focus on the linear axes of machine tools.Paper III proposes a semantic framework for predictive maintenance, and investigates means of acquiring relevant information from different sources (i.e., ontology-based data retrieval).Paper IV presents a method for data integration. The method is applied to data obtained from a real manufacturing setup. Simulation-based evaluation is used to compare results with a traditional time-based approach.Paper V presents the results from additional simulation-based experiments based on the method from Paper IV. The aim is to improve the method and provide additional information that can support maintenance decision-making (e.g., determining the optimal interval for inspections).The method developed in this thesis is applied to a population of linear axes from a set of similar multipurpose machine tools. The linear axes of machine tools are very important, as their performance directly affects machining quality. Measurements from circularity tests performed using a double ball-bar measuring device are combined with event and context information to build statistical failure and classification models. Based on those models, a decision-making process is proposed and evaluated. In the analysed case, the proposed approach leads to direct maintenance cost reduction of around 40 % compared to a time-based approach.
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