| 11. |
- Aalipour, Mojgan, et al.
(författare)
-
Human reliability assessment (HRA) in maintenance of production process : a case study
- 2016
-
Ingår i: International Journal of Systems Assurance Engineering and Management. - : Springer Science and Business Media LLC. - 0975-6809 .- 0976-4348. ; 7:2, s. 229-238
-
Tidskriftsartikel (refereegranskat)abstract
- Human reliability makes a considerable contribution to the maintenance performance, safety, and cost-efficiency of any production process. To improve human reliability, the causes of human errors should be identified and the probability of human errors should be quantified. Analysis of human error is very case-specific; the context of the field should be taken into account. The aim of this study is to identify the causes of human errors and improve human reliability in maintenance activities in the cable manufacturing industry. The central thrust of this paper is to employ the three most common HRA techniques—human error assessment and reduction technique, standardized plant analysis risk-human reliability, and Bayesian network—for estimating human error probabilities and then to check the consistency of the results obtained. The case study results demonstrated that the main causes of human error during maintenance activities are time pressure, lack of experience, and poor procedure. Moreover, the probabilities of human error, obtained by employing the three techniques, are similar and consistent
|
|
| 12. |
- Aalipour, Mojgan, et al.
(författare)
-
Identification of Factors affecting Human performance in Mining Maintenance tasks
- 2014
-
Ingår i: Proceedings of the 3rd international workshop and congress on eMaintenance. - Luleå : Luleå tekniska universitet. - 9789174399721 - 9789174399738 ; , s. 71-76
-
Konferensbidrag (refereegranskat)abstract
- This paper investigates the factors affecting humanperformance in maintenance task in mining sector. Theobjective is identify various factors and to classify them asdriving (strong driving power and weak dependence) anddependent factors (weak driving power and strongdependence). The factors were identified through literaturesurvey and are ranked using mean score of data questionnaire.The reliability of measures is pretested by applyingCronbach’s alpha coefficient to responses to a questionnairegiven to maintenance personnel. The interrelationshipsbetween human factors have been recognized by interpretivestructural modeling (ISM). Further, these factors have beenclassified using matrice d'impacts croises-multiplicationappliqué à un classement (MICMAC) analysing. This casestudy will figure out the factors affecting human performancefor deriving maintenance management insights to improveproductivity in the mining sector. Further, this understandingmay be helpful in framing the policies and strategies formining industry. Temperature, lighting, documentation,communication and fitness are driving factors. Moreover,Work layout, tools availability, complex tasks, time pressure,safety, boss decisions, training, fatigue and motivation havestrong driving power as well as high dependencies and itcomes under the category of linkage factors.
|
|
| 13. |
- Aalipour, Mojgan, et al.
(författare)
-
Work place factors effect on maintainability in challenging operating conditions
- 2015
-
Ingår i: 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). - Piscataway, NJ : IEEE Communications Society. - 9781467380669 - 9781467380669 ; , s. 767-771
-
Konferensbidrag (refereegranskat)abstract
- Some industries such as mining industry create complex and challenging work place for maintenance crews. For example in an underground mine, for some machines, heavy maintenance tasks must be performed on site in a limited workspace in a harsh environment, including dust and improper illumination. Such operating conditions can increase the health, safety, and environment (HSE) risk, reduce the availability of the machines and increase the life cycle cost of equipment. A review of current mining equipment design and maintenance procedure confirms that considerable reduction in HSE risk, as well as substantial cost savings, can be achieved by considering human factors. This study discusses the effect of workplace factors on the maintainability of mining equipment. It presents the results from questionnaires on the effect of work place factors on maintainability performance given to maintenance staff at two mines, one in northern Sweden and the other in Iran.
|
|
| 14. |
- Aaltonen, Harri, et al.
(författare)
-
A simulation environment for training a reinforcement learning agent trading a battery storage
- 2021
-
Ingår i: Energies. - : MDPI. - 1996-1073. ; 14:17
-
Tidskriftsartikel (refereegranskat)abstract
- Battery storages are an essential element of the emerging smart grid. Compared to other distributed intelligent energy resources, batteries have the advantage of being able to rapidly react to events such as renewable generation fluctuations or grid disturbances. There is a lack of research on ways to profitably exploit this ability. Any solution needs to consider rapid electrical phenomena as well as the much slower dynamics of relevant electricity markets. Reinforcement learning is a branch of artificial intelligence that has shown promise in optimizing complex problems involving uncertainty. This article applies reinforcement learning to the problem of trading batteries. The problem involves two timescales, both of which are important for profitability. Firstly, trading the battery capacity must occur on the timescale of the chosen electricity markets. Secondly, the real-time operation of the battery must ensure that no financial penalties are incurred from failing to meet the technical specification. The trading-related decisions must be done under uncertainties, such as unknown future market prices and unpredictable power grid disturbances. In this article, a simulation model of a battery system is proposed as the environment to train a reinforcement learning agent to make such decisions. The system is demonstrated with an application of the battery to Finnish primary frequency reserve markets.
|
|
| 15. |
- Aaltonen, Harri, et al.
(författare)
-
Bidding a Battery on Electricity Markets and Minimizing Battery Aging Costs: A Reinforcement Learning Approach
- 2022
-
Ingår i: Energies. - : MDPI. - 1996-1073. ; 15:14
-
Tidskriftsartikel (refereegranskat)abstract
- Battery storage is emerging as a key component of intelligent green electricitiy systems. The battery is monetized through market participation, which usually involves bidding. Bidding is a multiâ€objective optimization problem, involving targets such as maximizing market compensation and minimizing penalties for failing to provide the service and costs for battery aging. In this article, battery participation is investigated on primary frequency reserve markets. Reinforcement learning is applied for the optimization. In previous research, only simplified formulations of battery aging have been used in the reinforcement learning formulation, so it is unclear how the optimizer would perform with a real battery. In this article, a physicsâ€based battery aging model is used to assess the aging. The contribution of this article is a methodology involving a realistic battery simulation to assess the performance of the trained RL agent with respect to battery aging in order to inform the selection of the weighting of the aging term in the RL reward formula. The RL agent performs day-ahead bidding on the Finnish Frequency Containment Reserves for Normal Operation market, with the objective of maximizing market compensation, minimizing market penalties and minimizing aging costs.
|
|
| 16. |
|
|
| 17. |
|
|
| 18. |
- Aardal, Karen, et al.
(författare)
-
Decomposition principles applied to the dynamic production and work-force scheduling problem
- 1987
-
Ingår i: Engineering Costs and Production Economics. - 0167-188X .- 1878-4011. ; 12:1-4, s. 39-49
-
Tidskriftsartikel (refereegranskat)abstract
- One of the most important problems in the production and inventory planning field, is the scheduling of production and work force in a dynamic environment. Although this problem can be formulated as a linear program, it is often quite difficult to solve directly, due to its large scale. Instead, it might be fruitful to use a decomposition approach. Decomposition, in general, means decomposing a difficult problem into several easier, or a sequence of easier problems which are later coordinated to reconstruct the original problem.In this report we discuss several possibilities of applying the most common decomposition principles, namely Benders (primal) and Datnzig-Wolfe (dual), as well as a relatively new decomposition method, called cross decomposition, to the dynamic, multiproduct production and employment planning problem. A number of special cases are also presented.
|
|
| 19. |
- Aardal, Karen, et al.
(författare)
-
On the resemblance between the Kornai-Liptak and cross decomposition techniques for block-angular linear programs
- 1990
-
Ingår i: European Journal of Operational Research. - : Elsevier BV. - 0377-2217 .- 1872-6860. ; 46:3, s. 393-398
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper the resemblance is demonstrated between the master- and subproblems generated by the Kornai-Liptak algorithm and the subproblems obtained by using the cross decomposition method on linear optimization problems with block-angular structure. The significance of the similarity between these two algorithms becomes apparent considering the main disadvantage attributed to cross decomposition. In cross decomposition a master problem has to be solved from time to time since the subproblems alone do not always give a converging sequence of primal and dual solutions. But if the cross decomposition algorithm is modified in such a way that the successive primal and dual subproblem solutions are taken into consideration with equal weights, this results in the Kornai-Liptak algorithm for which convergence is guaranteed
|
|
| 20. |
|
|
