1. |
- Aslam, Tehseen, 1981-, et al.
(författare)
-
Towards an industrial testbed for holistic virtual production development
- 2018
-
Ingår i: Advances in Manufacturing Technology XXXII. - Amsterdam : IOS Press. - 9781614999010 - 9781614999027 ; , s. 369-374
-
Konferensbidrag (refereegranskat)abstract
- Virtual production development is adopted by many companies in the production industry and digital models and virtual tools are utilized for strategic, tactical and operational decisions in almost every stage of the value chain. This paper suggest a testbed concept that aims the production industry to adopt a virtual production development process with integrated tool chains that enables holistic optimizations, all the way from the overall supply chain performance down to individual equipment/devices. The testbed, which is fully virtual, provides a mean for development and testing of integrated digital models and virtual tools, including both technical and methodological aspects.
|
|
2. |
|
|
3. |
- Igelmo, Victor, 1992-, et al.
(författare)
-
Enabling Industrial Mixed Reality Using Digital Continuity : An Experiment Within Remanufacturing
- 2022
-
Ingår i: SPS2022. - Amsterdam; Berlin; Washington, DC : IOS Press. - 9781643682686 - 9781643682693 ; , s. 497-507
-
Konferensbidrag (refereegranskat)abstract
- In the digitalisation era, overlaying digital, contextualised information on top of the physical world is essential for an efficient operation. Mixed reality (MR) is a technology designed for this purpose, and it is considered one of the critical drivers of Industry 4.0. This technology has proven to have multiple benefits in the manufacturing area, including improving flexibility, efficacy, and efficiency. Among the challenges that prevent the big-scale implementation of this technology, there is the authoring challenge, which we address by answering the following research questions: (1) “how can we fasten MR authoring in a manufacturing context?” and (2) “how can we reduce the deployment time of industrial MR experiences?”. This paper presents an experiment performed in collaboration with Volvo within the remanufacturing of truck engines. MR seems to be more valuable for remanufacturing than for many other applications in the manufacturing industry, and the authoring challenge appears to be accentuated. In this experiment, product lifecycle management (PLM) tools are used along with internet of things (IoT) platforms and MR devices. This joint system is designed to keep the information up-to-date and ready to be used when needed. Having all the necessary data cascading from the PLM platform to the MR device using IoT prevents information silos and improves the system’s overall reliability. Results from the experiment show how the interconnection of information systems can significantly reduce development and deployment time. Experiment findings include a considerable increment in the complexity of the overall IT system, the need for substantial investment in it, and the necessity of having highly qualified IT staff. The main contribution of this paper is a systematic approach to the design of industrial MR experiences.
|
|
4. |
- Senington, Richard, et al.
(författare)
-
Monte Carlo Tree Search for online decision making in smart industrial production
- 2021
-
Ingår i: Computers in industry (Print). - : Elsevier. - 0166-3615 .- 1872-6194. ; 128, s. 1-10
-
Tidskriftsartikel (refereegranskat)abstract
- This paper considers the issue of rapid automated decision making in changing factory environments, situations including human-robot collaboration, mass customisation and the need to rapidly adapt activities to new conditions. The approach taken is to adapt the Monte Carlo Tree Search (MCTS) algorithm to provide online choices for the possible actions of machines and workers, interleaving them dynamically in response to the changing conditions of the production process. This paper describes how the MCTS algorithm has been adapted for use in production environments and then the proposed method is illustrated by two examples of the system in use, one simulated and one in a physical test cell.
|
|
5. |
- Syberfeldt, Anna, 1981-, et al.
(författare)
-
SIMULATION-GENERATED TRAINING DATA FOR IMPROVED PERFORMANCE OF AI-BASED INDUSTRIAL VISION SYSTEMS
- 2024
-
Ingår i: Industrial Simulation Conference. - : EUROSIS-ETI. - 9789492859303 ; , s. 83-87
-
Konferensbidrag (refereegranskat)abstract
- Quality inspections are essential in almost all manufacturing processes and can be undertaken using an automatic vision system. The main challenge when using AI-based vision systems is gathering enough training data for the AI to perform well. This study investigates the use of simulationgenerated data to address this challenge. A real-world industrial case study evaluates the feasibility of simulationgenerated images for training an AI to be used in an industrial vision system for quality inspection. Results from the study show that the approach has potential, but that simulationgenerated images cannot be used solely. However, real-world images must be mixed into the training data set to achieve satisfactory results.
|
|
6. |
- Andersson, Martin, 1981-, et al.
(författare)
-
Evolutionary Simulation Optimization of Personnel Scheduling
- 2014
-
Ingår i: 12th International Industrial Simulation Conference 2014. - : Eurosis. - 9789077381830 ; , s. 61-65
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a simulation-optimization system for personnel scheduling. The system is developed for the Swedish postal services and aims at finding personnel schedules that minimizes both total man hours and the administrative burden of the person responsible for handling schedules. For the optimization, the multi-objective evolutionary algorithm NSGA-II is implemented. The simulation-optimization system is evaluated on a real-world test case and results from the evaluation shows that the algorithm is successful in optimizing the problem.
|
|
7. |
- Andersson, My, et al.
(författare)
-
Improved interaction with collaborative robots - evaluation of event-specific haptic feedback in virtual reality
- 2024
-
Ingår i: Procedia Computer Science. - : Elsevier. - 1877-0509. ; 232, s. 1055-1064
-
Tidskriftsartikel (refereegranskat)abstract
- Industry 5.0 adopts a human-centric approach that views humans as a natural part of introducing new technology, such as collaborative robots. However, one of the main challenges in implementing collaborative robots is safety, including the sense of safety. Trust is also a primary challenge when establishing functional collaboration. Influencing factors includes experience and expertise, and research shows that Virtual Reality has the potential to perform such training. This research aims to investigate whether using virtual reality with appropriate feedback can be an effective platform for familiarization and training. In our experiment, we utilized haptic feedback from commercial Virtual Reality controllers to simulate physical interactions with collaborative robots. The experiment involved the participation of fifteen individuals. The results showed that participants regarded haptic feedback while moving as the most appropriate representation. This research aims to identify whether Virtual Reality with suitable feedback can serve as a familiarization and training platform.
|
|
8. |
- Andersson, Martin, 1981-, et al.
(författare)
-
Parameter tuned CMA-ES on the CEC'15 expensive problems
- 2015
-
Ingår i: 2015 IEEE Congress on Evolutionary Computation (CEC). - : IEEE conference proceedings. - 9781479974924 - 9781479974917 ; , s. 1950-1957
-
Konferensbidrag (refereegranskat)abstract
- Evolutionary optimization algorithms have parameters that are used to adapt the search strategy to suit different optimization problems. Selecting the optimal parameter values for a given problem is difficult without a-priori knowledge. Experimental studies can provide this knowledge by finding the best parameter values for a specific set of problems. This knowledge can also be constructed into heuristics (rule-of-thumbs) that can adapt the parameters for the problem. The aim of this paper is to assess the heuristics of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimization algorithm. This is accomplished by tuning CMA-ES parameters so as to maximize its performance on the CEC'15 problems, using a bilevel optimization approach that searches for the optimal parameter values. The optimized parameter values are compared against the parameter values suggested by the heuristics. The difference between specialized and generalized parameter values are also investigated.
|
|
9. |
- Andersson, Martin, 1981-, et al.
(författare)
-
Parameter Tuning of MOEAs Using a Bilevel Optimization Approach
- 2015
-
Ingår i: Evolutionary Multi-Criterion Optimization. - Cham : Springer International Publishing Switzerland. - 9783319159331 - 9783319159348 ; , s. 233-247
-
Konferensbidrag (refereegranskat)abstract
- The performance of an Evolutionary Algorithm (EA) can be greatly influenced by its parameters. The optimal parameter settings are also not necessarily the same across different problems. Finding the optimal set of parameters is therefore a difficult and often time-consuming task. This paper presents results of parameter tuning experiments on the NSGA-II and NSGA-III algorithms using the ZDT test problems. The aim is to gain new insights on the characteristics of the optimal parameter settings and to study if the parameters impose the same effect on both NSGA-II and NSGA-III. The experiments also aim at testing if the rule of thumb that the mutation probability should be set to one divided by the number of decision variables is a good heuristic on the ZDT problems. A comparison of the performance of NSGA-II and NSGA-III on the ZDT problems is also made.
|
|
10. |
- Bernedixen, Jacob
(författare)
-
Automated Bottleneck Analysis of Production Systems : Increasing the applicability of simulation-based multi-objective optimization for bottleneck analysis within industry
- 2018
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Manufacturing companies constantly need to explore new management strategies and new methods to increase the efficiency of their production systems and retain their competitiveness. It is of paramount importance to develop new bottleneck analysis methods that can identify the factors that impede the overall performance of their productionsystems so that the optimal improvement actions can be performed. Many of the bottleneck-related research methods developed in the last two decades are aimed mainly at detecting bottlenecks. Due to their sole reliance on historical data and lackof any predictive capability, they are less useful for evaluating the effect of bottleneck improvements.There is an urgent need for an efficient and accurate method of pinpointing bottlenecks, identifying the correct improvement actions and the order in which these should be carried out, and evaluating their effects on the overall system performance. SCORE (simulation-based constraint removal) is a novel method that uses simulation based multi-objective optimization to analyze bottlenecks. By innovatively formulating bottleneck analysis as a multi-objective optimization problem and using simulation to evaluate the effects of various combinations of improvements, all attainable, maximum throughput levels of the production system can be sought through a single optimization run. Additionally, post-optimality frequency analysis of the Pareto-optimal solutions can generate a rank order of the attributes of the resources required to achieve the target throughput levels. However, in its original compilation, SCORE has a very high computational cost, especially when the simulation model is complex with a large number of decision variables. Some tedious manual setup of the simulation based optimization is also needed, which restricts its applicability within industry, despite its huge potential. Furthermore, the accuracy of SCORE in terms of convergence in optimization theory and correctness of identifying the optimal improvement actions has not been evaluated scientifically.Building on previous SCORE research, the aim of this work is to develop an effective method of automated, accurate bottleneck identification and improvement analysis that can be applied in industry.The contributions of this thesis work include:(1) implementation of a versatile representation in terms of multiple-choice set variables and a corresponding constraint repair strategy into evolutionary multi-objective optimization algorithms;(2) introduction of a novel technique that combines variable screening enabled initializationof population and variable-wise genetic operators to support a more efficient search process;(3) development of an automated setup for SCORE to avoid the tedious manual creation of optimization variables and objectives;(4) the use of ranking distance metrics to quantify and visualize the convergence and accuracy of the bottleneck ranking generated by SCORE.All these contributions have been demonstrated and evaluated through extensive experiments on scalable benchmark simulation models as well as several large-scale simulation models for real-world improvement projects in the automotive industry.The promising results have proved that, when augmented with the techniques proposed in this thesis, the SCORE method can offer real benefits to manufacturing companies by optimizing their production systems.
|
|