| 1. |
- Hilletofth, Per
(författare)
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Demand-Supply Chain Management
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Purpose: This research aims to enhance the current understanding and knowledge of the demand-supply chain management (DSCM) concept by determining its elements, benefits, and requirements, as well as by analyzing key elements of the concept. Methodology: This research has utilized the case study strategy and the survey strategy, however, the case study strategy dominates. The case study research has involved five companies originating from Sweden and the collection of empirical data mainly from in-depth interviews with key persons representing senior and middle management. The survey research targeted the largest firms in Sweden and Finland and empirical data was collected through an online questionnaire. Findings: This research has established that the main elements of DSCM include market orientation, coordination of the demand and supply processes, viewing the demand and supply processes as being equally important, as well as value creation, differentiation, innovativeness, responsiveness, and cost-efficiency in the demand and supply processes. It has also been revealed that the main benefits of DSCM include enhanced competiveness, enhanced demand chain performance, as well as enhanced supply chain performance, while the main requirements of DSCM include organizational competences, company established principles, demand-supply chain collaboration, and information technology support. A key element of DSCM further investigated is differentiation focused supply chain design. It has been shown that these efforts can be organized into a process of five stages. In addition, it is important that this process is addressed in parallel with the new product development (NPD) process, that information is exchanged between them, and that they are directed on the basis of the same segmentation model. Another key element of DSCM further investigated is coordination between NPD and SCM. This research has identified several significant linkages between these management directions, which motivate the use of an integrative NPD process where the NPD functions are aligned with the main supply functions in the company and other sales-related functions supporting the commercialization. A final key element of DSCM further investigated is the significance of regarding the demand processes and the supply processes as being equally important. This research has revealed that logistics outsourcing can be risky, if it results in the supply processes being considered less important. Nevertheless, if senior management regards the outsourced processes as equally important as the in-house processes, the effect of logistics outsourcing on company strategies and direction in SCM could be reduced and logistics outsourcing could instead provide an opportunity to improve the design and differentiation of the supply chain. Research limitations/implications: This research has proposed, described, and further analyzed a demand-supply oriented management approach. Such a management approach stresses that the demand processes and the supply processes have to be coordinated and directed at an overlying level, in order to gain and sustain a competitive advantage in competitive and fragmented markets. This research is mainly explorative in nature, and more empirical data, from similar and other research settings, is needed to further validate the findings. Another limitation of the research is that it is essentially limited to Swedish companies (even if some Finnish companies are involved in the survey), however, many of the case companies have a large international presence and are among the top three in their industries, facts which provide some grounds for generalization. Practical implications: This research provides researchers and practitioners with insights into how to develop a demand-supply oriented business. It shows that companies should organize themselves around understanding how customer value is created and delivered, as well as how these processes and management directions can be coordinated. In order for this to occur, the demand and supply processes must be considered as being equally important and the firm needs to be managed jointly and in a coordinated manner by the demand- and supply-side of the company. It is also important that value creation is considered in both the demand and supply processes. Originality/value: Despite strong arguments from both researchers and practitioners for a demand-supply oriented management approach only a minority of companies appear to have effectively coordinated the demand and supply processes. This might be influenced by the lack of research examining how the demand and supply processes can be coordinated, what benefits can be gained by coordinating them, and what requirements are necessary to succeed. This research contributes by investigating these types of aspects further.
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| 2. |
- Grünloh, Christiane, 1980-, et al.
(författare)
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"why do they need to check me?" patient participation through ehealth and the doctor-patient relationship : Qualitative study
- 2018
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Ingår i: Journal of Medical Internet Research. - : J M I R Publications, Inc.. - 1438-8871. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Roles in the doctor-patient relationship are changing and patient participation in health care is increasingly emphasized. Electronic health (eHealth) services such as patient accessible electronic health records (PAEHRs) have been implemented to support patient participation. Little is known about practical use of PAEHR and its effect on roles of doctors and patients. Objective: This qualitative study aimed to investigate how physicians view the idea of patient participation, in particular in relation to the PAEHR system. Hereby, the paper aims to contribute to a deeper understanding of physicians' constructions of PAEHR, roles in the doctor-patient relationship, and levels and limits of involvement. Methods: A total of 12 semistructured interviews were conducted with physicians in different fields. Interviews were transcribed, translated, and a theoretically informed thematic analysis was performed. Results: Two important aspects were identified that are related to the doctor-patient relationship: roles and involvement. The physicians viewed their role as being the ones to take on the responsibility, determining treatment options, and to be someone who should be trusted. In relation to the patient's role, lack of skills (technical or regarding medical jargon), motives to read, and patients' characteristics were aspects identified in the interviews. Patients were often referred to as static entities disregarding their potential to develop skills and knowledge over time. Involvement captures aspects that support or hinder patients to take an active role in their care. Conclusions: Literature of at least two decades suggests an overall agreement that the paternalistic approach in health care is inappropriate, and a collaborative process with patients should be adopted. Although the physicians in this study stated that they, in principle, were in favor of patient participation, the analysis found little support in their descriptions of their daily practice that participation is actualized. As seen from the results, paternalistic practices are still present, even if professionals might not be aware of this. This can create a conflict between patients who strive to become more informed and their questions being interpreted as signs of critique and mistrust toward the physician. We thus believe that the full potential of PAEHRs is not reached yet and argue that the concept of patient empowerment is problematic as it triggers an interpretation of "power" in health care as a zero-sum, which is not helpful for the maintenance of the relationship between the actors. Patient involvement is often discussed merely in relation to decision making; however, this study emphasizes the need to include also sensemaking and learning activities. This would provide an alternative understanding of patients asking questions, not in terms of "monitoring the doctor" but to make sense of the situation.
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| 3. |
- Linnéusson, Gary, et al.
(författare)
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In Need for Better Maintenance Cost Modelling to Support the Partnership with Manufacturing
- 2016. - 1
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Ingår i: Current Trends in Reliability, Availability, Maintainability and Safety. - Cham : Springer. - 9783319235967 - 9783319235974 ; , s. 263-282
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The problem of maintenance consequential costs has to be dealt with in manufacturing and is core of this paper. The need of sustainable partnership between manufacturing and maintenance is addressed. Stuck in a best practice thinking, applying negotiation as a method based on power statements in the service level agreement, the common best possible achievable goal is put on risk. Instead, it may enforce narrow minded sub optimized thinking even though not intended so. Unfortunately, the state of origin is not straightforward business. Present maintenance cost modelling is approached, however limits to its ability to address the dynamic complexity of production flows are acknowledged. The practical problem to deal with is units put together in production flows; in which downtime in any unit may or may not result in decreased throughput depending on its set up. In this environment accounting consequential costs is a conundrum and a way forward is suggested. One major aspect in the matter is the inevitable need of shift in mind, from perspective thinking in maintenance and manufacturing respectively towards shared perspectives, nourishing an advantageous sustainable partnership.
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| 4. |
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| 5. |
- Ruiz Zúñiga, Enrique, 1986-, et al.
(författare)
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A simulation-based multi-objective optimization approach for production and logistics considering the production layout
- 2016
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Ingår i: Proceedings of the 7th Swedish Production Symposium.
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Konferensbidrag (refereegranskat)abstract
- Manufacturing sectors in Sweden have a long tradition and represent a significant share of the national gross domestic product and the export values. Most of the Swedish manufacturing companies have gone through a modernization and adaptation process in order to be able to compete on a globalized market. Many plants, however, still have non-optimized shop floors as a consequence of the shop floors being adapted over time without redesigning its production and logistics flows and with a lack of an overall strategy. To support the optimization of shop floors, this paper suggests the combined use of Discrete-Event Simulation and Simulation-Based Multi-objective Optimization. The aim of the paper is to analyze a simulation methodology that supports the optimization of shop floors by considering production and logistics flows along with the shop floor layout. The methodology is intended to contribute to significantly increase the productivity and efficiency of the Swedish manufacturing industry and help companies to survive on the globalized market. Through a case study, the paper shows that the proposed methodology is useful in practice and that it provides a decision support system for manufacturing companies.
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| 6. |
- Ruiz Zúñiga, Enrique, 1986-, et al.
(författare)
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Production Logistics Design and Development Support : A Simulation-Based Optimization Case Study (WIP)
- 2016
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Ingår i: SummerSim'16, 2016 July 24-27, Palais des congres de Montreal (Montreal Convention Center) | Montreal, Quebec, Canada. - : The Society for Modeling and Simulation International. - 9781510824249 ; , s. 56:1-56:6
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Konferensbidrag (refereegranskat)abstract
- Manufacturing sectors in Sweden have a long history that leads to common non-optimized flows on the shop floor. Especially when having a really high product mix and a low-volume of customized products, a great deal of effort with respect to flow optimization is needed to stay present and compete in the globalized market. The goal of this project is to support the design and development of the implementation of new production systems and logistics flows considering the shop floor plant layout of a Swedish middle-size water pumps factory. In this paper, with the help of different types of simulation models and optimization, some results of a new technologically adapted production line are analyzed and relevant information and potential improvements in the production are found. The further development of optimization studies using the exiting simulation models is stated as ongoing and future work. The obtained and potential results can serve for decision makers and stakeholders to apply changes and adaptations in the system considering the mid and long term goals of the company.
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| 7. |
- Mellin, Jonas, et al.
(författare)
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The effect of optimizing engine control on fuel consumption and roll amplitude in ocean-going vessels : An experimental study
- 2015
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We use data-generated models based on data from experiments of an ocean-going vessel to study the effect of optimizing fuel consumption. The optimization is an add-on module to the existing diesel-engine fuel-injection control built by Q-TAGG R&D AB. The work is mainly a validation of knowledge-based models based on a priori knowledge from physics. The results from a simulation-based analysis of the predictive models built on data agree with the results based on knowledge-based models in a companion study. This indicates that the optimization algorithm saves fuel. We also address specific problems of adapting data to existing machine learning methods. It turns out that we can simplify the problem by ignoring the auto-correlative effects in the time series by employing low-pass filters and resampling techniques. Thereby we can use mature and robust classification techniques with less requirements on the data to demonstrate that fuel is saved compared to the full-fledged time series analysis techniques which are harder to use. The trade-off is the accuracy of the result, that is, it is hard to tell exactly how much fuel is saved. In essence, however, this process can be automated due to its simplicity.
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| 8. |
- Siegmund, Florian, et al.
(författare)
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A Ranking and Selection Strategy for Preference-based Evolutionary Multi-objective Optimization of Variable-Noise Problems
- 2016
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Ingår i: 2016 IEEE Congress on Evolutionary Computation (CEC). - : IEEE conference proceedings. - 9781509006236 - 9781509006243 - 9781509006229 ; , s. 3035-3044
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Konferensbidrag (refereegranskat)abstract
- In simulation-based Evolutionary Multi-objective Optimization the number of simulation runs is very limited, since the complex simulation models require long execution times. With the help of preference information, the optimization result can be improved by guiding the optimization towards relevant areas in the objective space, for example with the R-NSGA-II algorithm [9], which uses a reference point specified by the decision maker. When stochastic systems are simulated, the uncertainty of the objective values might degrade the optimization performance. By sampling the solutions multiple times this uncertainty can be reduced. However, resampling methods reduce the overall number of evaluated solutions which potentially worsens the optimization result. In this article, a Dynamic Resampling strategy is proposed which identifies the solutions closest to the reference point which guides the population of the Evolutionary Algorithm. We apply a single-objective Ranking and Selection resampling algorithm in the selection step of R-NSGA-II, which considers the stochastic reference point distance and its variance to identify the best solutions. We propose and evaluate different ways to integrate the sampling allocation method into the Evolutionary Algorithm. On the one hand, the Dynamic Resampling algorithm is made adaptive to support the EA selection step, and it is customized to be used in the time-constrained optimization scenario. Furthermore, it is controlled by other resampling criteria, in the same way as other hybrid DR algorithms. On the other hand, R-NSGA-II is modified to rely more on the scalar reference point distance as fitness function. The results are evaluated on a benchmark problem with variable noise landscape.
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| 9. |
- Siegmund, Florian
(författare)
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Dynamic Resampling for Preference-based Evolutionary Multi-objective Optimization of Stochastic Systems : Improving the efficiency of time-constrained optimization
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In preference-based Evolutionary Multi-objective Optimization (EMO), the decision maker is looking for a diverse, but locally focused non-dominated front in a preferred area of the objective space, as close as possible to the true Pareto-front. Since solutions found outside the area of interest are considered less important or even irrelevant, the optimization can focus its efforts on the preferred area and find the solutions that the decision maker is looking for more quickly, i.e., with fewer simulation runs. This is particularly important if the available time for optimization is limited, as is the case in many real-world applications. Although previous studies in using this kind of guided-search with preference information, for example, withthe R-NSGA-II algorithm, have shown positive results, only very few of them considered the stochastic outputs of simulated systems.In the literature, this phenomenon of stochastic evaluation functions is sometimes called noisy optimization. If an EMO algorithm is run without any countermeasure to noisy evaluation functions, the performance will deteriorate, compared to the case if the true mean objective values are known. While, in general, static resampling of solutions to reduce the uncertainty of all evaluated design solutions can allow EMO algorithms to avoid this problem, it will significantly increase the required simulation time/budget, as many samples will be wasted on candidate solutions which are inferior. In comparison, a Dynamic Resampling (DR) strategy can allow the exploration and exploitation trade-off to be optimized, since the required accuracy about objective values varies between solutions. In a dense, converged population, itis important to know the accurate objective values, whereas noisy objective values are less harmful when an algorithm is exploring the objective space, especially early in the optimization process. Therefore, a well-designed Dynamic Resampling strategy which resamples the solution carefully, according to the resampling need, can help an EMO algorithm achieve better results than a static resampling allocation.While there are abundant studies in Simulation-based Optimization that considered Dynamic Resampling, the survey done in this study has found that there is no related work that considered how combinations of Dynamic Resampling and preference-based guided search can further enhance the performance of EMO algorithms, especially if the problems under study involve computationally expensive evaluations, like production systems simulation. The aim of this thesis is therefore to study, design and then to compare new combinations of preference-based EMO algorithms with various DR strategies, in order to improve the solution quality found by simulation-based multi-objective optimization with stochastic outputs, under a limited function evaluation or simulation budget. Specifically, based on the advantages and flexibility offered by interactive, reference point-based approaches, studies of the performance enhancements of R-NSGA-II when augmented with various DR strategies, with increasing degrees of statistical sophistication, as well as several adaptive features in terms of optimization parameters, have been made. The research results have clearly shown that optimization results can be improved, if a hybrid DR strategy is used and adaptive algorithm parameters are chosen according to the noise level and problem complexity. In the case of a limited simulation budget, the results allow the conclusions that both decision maker preferences and DR should be used at the same time to achieve the best results in simulation-based multi-objective optimization.
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| 10. |
- Siegmund, Florian, 1981-, et al.
(författare)
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Hybrid Dynamic Resampling Algorithms for Evolutionary Multi-objective Optimization of Invariant-Noise Problems
- 2016
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Ingår i: Applications of Evolutionary Computation. - Cham : Springer International Publishing. - 9783319311524 - 9783319311531 ; , s. 311-326
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Konferensbidrag (refereegranskat)abstract
- In Simulation-based Evolutionary Multi-objective Optimization (EMO) the available time for optimization usually is limited. Since many real-world optimization problems are stochastic models, the optimization algorithm has to employ a noise compensation technique for the objective values. This article analyzes Dynamic Resampling algorithms for handling the objective noise. Dynamic Resampling improves the objective value accuracy by spending more time to evaluate the solutions multiple times, which tightens the optimization time limit even more. This circumstance can be used to design Dynamic Resampling algorithms with a better sampling allocation strategy that uses the time limit. In our previous work, we investigated Time-based Hybrid Resampling algorithms for Preference-based EMO. In this article, we extend our studies to general EMO which aims to find a converged and diverse set of alternative solutions along the whole Pareto-front of the problem. We focus on problems with an invariant noise level, i.e. a flat noise landscape.
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