| 1. |
- Rabet, Rahmat, et al.
(författare)
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A simheuristic approach towards supply chain scheduling : Integrating production, maintenance and distribution
- 2024
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Ingår i: Applied Soft Computing. - : Elsevier. - 1568-4946 .- 1872-9681. ; 153
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Tidskriftsartikel (refereegranskat)abstract
- This study attempts to integrate production, maintenance, and delivery operations among supply chain members. Despite numerous studies in the field of supply chain management, researchers have often overlooked crucial aspects, such as uncertainties in demand and production. For instance, the significant impact of maintenance activities on production flow has been underrepresented in supply chain management literature. This study investigates these gaps in the context of a fertilizer producer case study, which is characterized by seasonal demand and the functional silos syndrome due to old-fashioned management approaches. This study proposes a mathematical model and two multi-objective simheuristics for the Integrated Production, Maintenance, and Distribution Scheduling Problem (IPMDSP) considering demand variation for multiple products and product delivery time-windows using a heterogeneous fleet of vehicles. The IPMDSP is solved using the ϵ-constraint method and simheuristics linking the simulation model to customized and tuned versions of Particle Swarm Optimization (MOPSO) and the Non-dominated Sorting Genetic Algorithm (NSGA-II). The optimization objectives include minimizing maintenance duration, distribution costs, and customer dissatisfaction due to delivery tardiness. The results demonstrate the superiority of the simheuristic empowered by NSGA-II over the MOPSO in solving the IPMDSP. The comparison between the performance of deterministic and stochastic approaches in addressing the problem reveals that neglecting uncertainty caused by maintenance activities can lead to an increase in optimization objectives. Furthermore, the proposed simheuristics achieved significant improvements in minimizing objectives in solving the fertilizer producer case study.
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| 2. |
- Salin, Hannes, et al.
(författare)
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A Gap Analysis of the Adoption Maturity of Certificateless Cryptography in Cooperative Intelligent Transportation Systems
- 2023
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Ingår i: Journal of Cybersecurity and Privacy. - : MDPI. - 2624-800X .- 2624-800X. ; 3:3, s. 591-609
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Tidskriftsartikel (refereegranskat)abstract
- Cooperative Intelligent Transport Systems (C-ITSs) are an important development for society. C-ITSs enhance road safety, improve traffic efficiency, and promote sustainable transportation through interconnected and intelligent communication between vehicles, infrastructure, and traffic-management systems. Many real-world implementations still consider traditional Public Key Infrastructures (PKI) as the underlying trust model and security control. However, there are challenges with the PKI-based security control from a scalability and revocation perspective. Lately, certificateless cryptography has gained research attention, also in conjunction with C-ITSs, making it a new type of security control to be considered. In this study, we use certificateless cryptography as a candidate to investigate factors affecting decisions (not) to adopt new types of security controls, and study its current gaps, key challenges and possible enablers which can influence the industry. We provide a qualitative study with industry specialists in C-ITSs, combined with a literature analysis of the current state of research in certificateless cryptographic in C-ITS. It was found that only 53% of the current certificateless cryptography literature for C-ITSs in 2022–2023 provide laboratory testing of the protocols, and 0% have testing in real-world settings. However, the trend of research output in the field has been increasing linearly since 2016 with more than eight times as many articles in 2022 compared to 2016. Based on our analysis, using a five-phased Innovation-Decision Model, we found that key reasons affecting adoption are: availability of proof-of-concepts, knowledge beyond current best practices, and a strong buy-in from both stakeholders and standardization bodies.
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| 3. |
- Trapero, Juan R., et al.
(författare)
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On the identification of sales forecasting models in the presence of promotions
- 2015
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Ingår i: Journal of the Operational Research Society. - : Taylor & Francis. - 0160-5682 .- 1476-9360. ; 66:2, s. 299-307
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Tidskriftsartikel (refereegranskat)abstract
- Shorter product life cycles and aggressive marketing, among other factors, have increased the complexity of sales forecasting. Forecasts are often produced using a Forecasting Support System that integrates univariate statistical forecasting with managerial judgment. Forecasting sales under promotional activity is one of the main reasons to use expert judgment. Alternatively, one can replace expert adjustments by regression models whose exogenous inputs are promotion features (price, display, etc). However, these regression models may have large dimensionality as well as multicollinearity issues. We propose a novel promotional model that overcomes these limitations. It combines Principal Component Analysis to reduce the dimensionality of the problem and automatically identifies the demand dynamics. For items with limited history, the proposed model is capable of providing promotional forecasts by selectively pooling information across established products. The performance of the model is compared against forecasts provided by experts and statistical benchmarks, on weekly data; outperforming both substantially.
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| 4. |
- Gerdes, Mike, et al.
(författare)
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Decision Trees and the Effects of Feature Extraction Parameters for Robust Sensor Network Design
- 2017
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Ingår i: Eksploatacja i Niezawodność – Maintenance and Reliability. - : Polskie Naukowo - Techniczne Towarzystwo Eksploatacyjne. - 1507-2711 .- 2956-3860. ; 19:1, s. 31-42
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Tidskriftsartikel (refereegranskat)abstract
- Reliable sensors and information are required for reliable condition monitoring. Complex systems are commonly monitored by many sensors for health assessment and operation purposes. When one of the sensors fails, the current state of the system cannot be calculated in same reliable way or the information about the current state will not be complete. Condition monitoring can still be used with an incomplete state, but the results may not represent the true condition of the system. This is especially true if the failed sensor monitors an important system parameter. There are two possibilities to handle sensor failure. One is to make the monitoring more complex by enabling it to work better with incomplete data; the other is to introduce hard or software redundancy. Sensor reliability is a critical part of a system. Not all sensors can be made redundant because of space, cost or environmental constraints. Sensors delivering significant information about the system state need to be redundant, but an error of less important sensors is acceptable. This paper shows how to calculate the significance of the information that a sensor gives about a system by using signal processing and decision trees. It also shows how signal processing parameters influence the classification rate of a decision tree and, thus, the information. Decision trees are used to calculate and order the features based on the information gain of each feature. During the method validation, they are used for failure classification to show the influence of different features on the classification performance. The paper concludes by analysing the results of experiments showing how the method can classy different errors with a 75% probability and how different feature extraction options influence the information gain.
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| 5. |
- Gerdes, Mike, et al.
(författare)
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Fuzzy condition monitoring of recirculation fans and filters
- 2016
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Ingår i: International Journal of Systems Assurance Engineering and Management. - : Springer. - 0975-6809 .- 0976-4348. ; 7:4, s. 469-479
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Tidskriftsartikel (refereegranskat)abstract
- A reliable condition monitoring is needed to be able to predict faults. Pattern recognition technologies are often used for finding patterns in complex systems. Condition monitoring can also benefit from pattern recognition. Many pattern recognition technologies however only output the classification of the data sample but do not output any information about classes that are also very similar to the input vector. This paper presents a concept for pattern recognition that outputs similarity values for decision trees. Experiments confirmed that the method works and showed good classification results. Different fuzzy functions were evaluated to show how the method can be adapted to different problems. The concept can be used on top of any normal decision tree algorithms and is independent of the learning algorithm. The goal is to have the probabilities of a sample belonging to each class. Performed experiments showed that the concept is reliable and it also works with decision tree forests (which is shown during this paper) to increase the classification accuracy. Overall the presented concept has the same classification accuracy than a normal decision tree but it offers the user more information about how certain the classification is.
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| 6. |
- Gerdes, M., et al.
(författare)
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Genetic algorithms and decision trees for condition monitoring and prognosis of A320 aircraft air conditioning
- 2017
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Ingår i: Insight. - : British Institute of Non-Destructive Testing. - 1354-2575 .- 1754-4904. ; 59:8, s. 424-433
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Tidskriftsartikel (refereegranskat)abstract
- Unscheduled maintenance is a large cost driver for airlines, but condition monitoring and prognosis can reduce the number of unscheduled maintenance actions. This paper discusses how condition monitoring can be introduced into most systems by adopting a data-driven approach and using existing data sources. The goal is to forecast the remaining useful life (RUL) of a system based on various sensor inputs. Decision trees are used to learn the characteristics of a system. The data for the decision tree training and classification are processed by a generic parametric signal analysis. To obtain the best classification results for the decision tree, the parameters are optimised by a genetic algorithm. A forest of three different decision trees with different signal analysis parameters is used as a classifier. The proposed method is validated with data from an A320 aircraft from Etihad Airways. Validation shows that condition monitoring can classify the sample data into ten predetermined categories, representing the total useful life (TUL) in 10% steps. This is used to predict the RUL. There are 350 false classifications out of 850 samples. Noise reduction reduces the outliers to nearly zero, making it possible to correctly predict condition. It is also possible to use the classification output to detect a maintenance action in the validation data.
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| 7. |
- Schaer, Oliver, et al.
(författare)
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Demand forecasting with user-generated online information
- 2019
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Ingår i: International Journal of Forecasting. - : Elsevier. - 0169-2070 .- 1872-8200. ; 35:1, s. 197-212
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Tidskriftsartikel (refereegranskat)abstract
- Recently, there has been substantial research on the augmentation of aggregate forecasts with individual consumer data from internet platforms, such as search traffic or social network shares. Although the majority of studies have reported increases in accuracy, many exhibit design weaknesses, including a lack of adequate benchmarks or rigorous evaluation. Furthermore, their usefulness over the product life-cycle has not been investigated, even though this may change, as consumers may search initially for pre-purchase information, but later for after-sales support. This study begins by reviewing the relevant literature, then attempts to support the key findings using two forecasting case studies. Our findings are in stark contrast to those in the previous literature, as we find that established univariate forecasting benchmarks, such as exponential smoothing, consistently perform better those that include online information. Our research underlines the need for a thorough forecast evaluation and argues that the usefulness of online platform data for supporting operational decisions may be limited.
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| 8. |
- Schmidt, Bernard, 1981-, et al.
(författare)
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Context preparation for predictive analytics – a case from manufacturing industry
- 2017
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Ingår i: Journal of Quality in Maintenance Engineering. - : Emerald Publishing Limited. - 1355-2511 .- 1758-7832. ; 23:3, s. 341-354
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Tidskriftsartikel (refereegranskat)abstract
- PurposeThe purpose of this paper is to exemplify and discuss the context aspect for predictive analytics where in parallel condition monitoring (CM) measurements data and information related to the context are gathered and analysed.Design/methodology/approachThis paper is based on an industrial case study, conducted in a manufacturing company. The linear axis of a machine tool has been selected as an object of interest. Available data from different sources have been gathered and a new CM function has been implemented. Details about performed steps of data acquisition and selection are provided. Among the obtained data, health indicators and context-related information have been identified.FindingsMultiple sources of relevant contextual information have been identified. Performed analysis discovered the deviations in operational conditions when the same machining operation is repeatedly performed.Originality/valueThis paper shows the outcomes from a case study in real word industrial setup. A new visualisation method of gathered data is proposed to support decision-making process.
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| 9. |
- André, Alann, 1980, et al.
(författare)
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Application of fracture mechanics to predict the failure load of adhesive joints used to bond CFRP laminates to steel members
- 2012
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Ingår i: Construction and Building Materials. - : Elsevier BV. - 0950-0618 .- 1879-0526. ; 27:1, s. 331-340
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Tidskriftsartikel (refereegranskat)abstract
- The use of bolted or welded elements to upgrade metallic structures has been a common practice for many years. Moreover, the use of adhesively bonded carbon fiber reinforced polymer (CFRP) laminates, as an alternative method, has attracted a great deal of attention in recent years. One important aspect of the design of adhesive joints used to bond CFRP laminates to steel substrates is the determination of the properties of the CFRP/adhesive/steel interfaces, which have not yet been established in codes or standards. The purpose of this paper is experimentally to determine the fracture properties of the adhesive material and to evaluate the accuracy of numerical methods using this information, in order to predict the strength of adhesive joints in steel members bonded with CFRP laminates. The results from four series of experimental tests are compared with numerical results and discussed in terms of load-bearing capacity and failure modes.
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| 10. |
- Aslam, Tehseen, et al.
(författare)
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Combining system dynamics and multi-objective optimization with design space reduction
- 2016
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Ingår i: Industrial management & data systems. - : Emerald Group Publishing Limited. - 0263-5577 .- 1758-5783. ; 116:2, s. 291-321
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Tidskriftsartikel (refereegranskat)abstract
- Purpose The purpose of this study is to introduce an effective methodology for obtaining Pareto-optimal solutions, when combining System Dynamics (SD) and Multi-Objective Optimization (MOO) for supply chain problems.Design/methodology/approach This paper proposes a new approach that combines SD and MOO within a simulation-based optimization framework to generate the efficient frontier that supports decision- making in SupplyChain Management (SCM). It also addresses the issue of the curse of dimensionality, commonly found in practical optimization problems, through design space reduction.Findings The integrated MOO and SD approach has been shown to be very useful in revealing how the decision variables in the Beer Game affect the optimality of the three common SCM objectives, namely, the minimization of inventory, backlog, and the bullwhip effect. The results of the in-depth Beer Game study clearly show that these three optimization objectives are in conflict with each other, in the sense that a supply chain manager cannot minimize the bullwhip effect without increasing the total inventory and total backlog levels.Practical implications Having a methodology that enables the effective generation of optimal trade-off solutions, in terms of computational cost, time, as well as solution diversity and intensification, not only assists decision makers to make decisions on time, but also presents a diverse and intense solution set to choose from.Originality/value This paper presents a novel supply chain MOO methodology that helps to find Pareto-optimal solutions in a more effective manner. In order to do so, the methodology tackles the so-called curse of dimensionality, by reducing the design space and focusing the search of the optimization to regions of interest. Together with design space reduction, it is believed that the integrated SD and MOOapproach can provide an innovative and efficient method for the design and analysis of manufacturing supply chain systems in general.
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