| 1. |
- Aslam, Tehseen, 1981-, et al.
(author)
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Education of the Future : Learnings and Experiences from Offering Education to Industry Professionals
- 2022
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In: SPS2022. - Amsterdam; Berlin; Washington, DC : IOS Press. - 9781643682686 - 9781643682693 ; , s. 665-676
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Conference paper (peer-reviewed)abstract
- Digitalization is forcing the industry to rethink current practices in all business domains, pushing for a digital transformation of business and operations at a high rate and, thus, paving the way for new business models and making others redundant. For small and medium-sized companies (SME), in particular, it is an enormous challenge to keep up with the pace of technological development. Several initiatives have argued the industry’s need for continuous digitalization, innovation, transformation ability, and future skills and competencies development. However, the advancement of the Swedish industry in this area has been uneven, where larger organizations have begun their digital transformation journey to some extent, but SMEs risk falling behind. In addition to the technological transformation, the challenges regarding the industries’ skills supply need to be solved, where a workforce with the right competencies, knowledge, and skill sets are equally, if not more, important for remaining competitive. One of the key elements to face these challenges in the companies will be to recruit knowledgeable employees or re-skill the existing ones. Efficient access to relevant knowledge and skills is still a major concern for companies that will surely affect their competitiveness for a long time to come. This paper elaborates on the opportunities and challenges that Swedish universities face in the context of lifelong learning and education for industry professionals. The paper presents results and experiences gained from a lifelong learning project for industry professionals at the University of Skövde in collaboration with ten industry partners. The results from the project show that in addition to pedagogical methods, current structures and policies within academia need to be further developed to effectively serve industry professionals. The paper also presents a concept of education for industry professionals in the lifelong learning context based on the results and experience gained from the project.
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| 2. |
- Brekke, Morten, et al.
(author)
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Flexible learning and teaching : Thematic Peer Group Report
- 2024
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Reports (other academic/artistic)abstract
- European higher education institutions (HEIs) are facing increasing demands for more flexible learning and flexibility in learning paths.This report from a 2023 European University Association Learning & Teaching Thematic Peer Group on “Flexible learning and teaching” explores the complexity of implementing flexible learning at HEIs, starting by defining what it means and entails for the institution, and its members and entities (staff, students, leadership, faculties). With the view that the development of flexible learning is an essential condition for the future of learning at universities, the group identified challenges and examples of practice, and offered recommendations for institutions to reflect on their strategy and build capacity for flexible learning.
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| 3. |
- Goienetxea Uriarte, Ainhoa, 1983-
(author)
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Bringing Together Lean, Simulation and Optimization : Defining a framework to support decision-making in system design and improvement
- 2019
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Doctoral thesis (other academic/artistic)abstract
- The rapid changes in the market including globalization, the requirement for personalizedproducts and services by the customers, shorter product life-cycles, the exponential growthof technological advances, and the demographical changes, will demand organizations toeffectively improve and design their systems in order to survive. This is the actual paradigmcharacterizing the industrial and service sectors. This scenario presents a considerablechallenge to decision makers who will need to decide about how to design and improve amore than ever complex system without compromising the quality of the decision taken.Lean, being a widely applied management philosophy with very powerful principles, itsmethods and tools are static in nature and have some limitations when it comes to the designand improvement of complex and dynamic systems. Some authors have proposed thecombined use of simulation with Lean in order to overcome these limitations. Furthermore,optimization and post-optimization tools coupled to simulation, provide knowledge aboutoptimal or nearly optimal system configurations to choose from. However, even if Leanprinciples, methods and tools, as well as simulation and optimization, pursue the objectiveof supporting organizations regarding system design and improvement, a bilateral approachfor their combination and its benefits have barely been addressed in the literature.Many studies focus only on how specific Lean tools and simulation can be combined, treatingLean purely as a toolbox and not considering how Lean can support the simulation process.The aim of this research is to address this knowledge gap by analyzing the mutualbenefits and presenting a framework for combining Lean, simulation and optimization tobetter support decision makers in system design and improvement where the limitationsof Lean tools and simulation are overcome by their combination. This framework includesa conceptual framework explaining the relationships between the Lean philosophy, methodsand tools with simulation and optimization; the purposes for this combination and stepby step processes to achieve these purposes; the identification of the roles involved in eachprocess; a maturity model providing guidelines on how to implement the framework; existingbarriers for the implementation; and ethical considerations to take into account. Anindustrial handbook has also been written which explains how to deploy the framework.The research has been conducted in three main stages including an analysis of the literatureand the real-world needs, the definition and formulation of the framework, and finally, itsevaluation in real-world projects and with subject matter experts. The main contributionof this research is the reflection provided on the bilateral benefits of the combination, aswell as the defined and evaluated framework, which will support decision makers take qualitydecisions in system design and improvement even in complex scenarios.
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| 4. |
- Goienetxea Uriarte, Ainhoa, 1983-
(author)
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Bringing together Lean, simulation and optimization in a framework for system design and improvement
- 2018
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In: Proceedings of the Winter Simulation Conference, Gothenburg, 9-12 December, 2018. - Piscataway, New Jersey : IEEE. ; , s. 4132-4133
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Conference paper (peer-reviewed)abstract
- Is it beneficial to combine lean, simulation and optimization? And if so, how can they be combined for decision-making support in system design and improvement? This research proposes a framework that sets the basis for achieving beneficial interactions between the lean philosophy, methods and tools, and simulation-based optimization. A framework that gives the users the possibility to get better system understanding, conduct a deeper system analysis, and attain an optimal system design and improvement, and thereby, get better foundation for sustainable long time improvement. The framework has been tested in several realworld case studies. Moreover, surveys have been conducted to evaluate the perception of subject matter experts about its usefulness, as well as its usability and perceived quality by end users and decision makers, all of them reporting very positive results.
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| 5. |
- Goienetxea Uriarte, Ainhoa, 1983-, et al.
(author)
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How can decision makers be supported in the improvement of an emergency department? : A simulation, optimization and data mining approach
- 2017
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In: Operations Research for Health Care. - : Elsevier. - 2211-6923 .- 2211-6931. ; 15, s. 102-122
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Journal article (peer-reviewed)abstract
- The improvement of emergency department processes involves the need to take into considerationmultiple variables and objectives in a highly dynamic and unpredictable environment, which makes thedecision-making task extremely challenging. The use of different methodologies and tools to support thedecision-making process is therefore a key issue. This article presents a novel approach in healthcarein which Discrete Event Simulation, Simulation-Based Multi-Objective Optimization and Data Miningtechniques are used in combination. This methodology has been applied for a system improvementanalysis in a Swedish emergency department. As a result of the project, the decision makers were providedwith a range of nearly optimal solutions and design rules which reduce considerably the length of stayand waiting times for emergency department patients. These solutions include the optimal number ofresources and the required level of improvement in key processes. The article presents and discussesthe benefits achieved by applying this methodology, which has proven to be remarkably valuable fordecision-making support, with regard to complex healthcare system design and improvement.
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| 6. |
- Goienetxea Uriarte, Ainhoa, 1983-, et al.
(author)
-
Improving the material flow of a manufacturing company via lean, simulation and optimization
- 2017
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In: IEEE International Conference on Industrial Engineering and Engineering Management. - : IEEE. - 9781538609484 - 9781538609477 - 9781538609491 ; , s. 1245-1250
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Conference paper (peer-reviewed)abstract
- Companies are continuously working towards system and process improvement to remain competitive in a global market. There are different methods that support companies in the achievement of that goal. This paper presents an innovative process that combines lean, simulation and optimization to improve the material flow of a manufacturing company. A description of each step of the process details the lean tools and principles taken into account, as well as the results achieved by the application of simulation and optimization. The project resulted in an improved layout and material flow that employs an automated guided vehicle. In addition, lean wastes related to transport, inventory levels as well as waiting times were reduced. The utilization of the process that combines lean, simulation and optimization was considered valuable for the success of the project.
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| 7. |
- Goienetxea Uriarte, Ainhoa, 1983-, et al.
(author)
-
Introducing simulation and optimization in the Lean continuous improvement standards in an automotive company
- 2019
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In: Proceedings of the Winter Simulation Conference, Gothenburg, December 9-12, 2018. - Piscataway, New Jersey : IEEE. - 9781538665725 - 9781538665701 - 9781538665718 - 9781538665732 ; , s. 3352-3363
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Conference paper (peer-reviewed)abstract
- The highly competitive automobile market requires automotive companies to become efficient by continuously improving their production systems. This paper presents a case study where simulationbased optimization (SBO) was employed as a step within a Value Stream Mapping event. The aim of the study was to promote the use of SBO to strengthen the continuous improvement work of the company. The paper presents all the key steps performed in the study, including the challenges faced and a reflection on how to introduce SBO as a powerful tool within the lean continuous improvement standards.
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| 8. |
- Goienetxea Uriarte, Ainhoa, 1983-, et al.
(author)
-
Lean, Simulation and Optimization : A Win-Win combination
- 2016
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In: Proceedings of the 2015 Winter Simulation Conference. - Piscataway, New Jersey : IEEE Computer Society. - 9781467397438 - 9781467397414 - 9781467397421 ; , s. 2227-2238
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Conference paper (peer-reviewed)abstract
- Lean and simulation analysis are driven by the same objective, how to better design and improve processes making the companies more competitive. The adoption of lean has been widely spread in companies from public to private sectors and simulation is nowadays becoming more and more popular. Several authors have pointed out the benefits of combining simulation and lean, however, they are still rarely used together in practice. Optimization as an additional technique to this combination is even a more powerful approach especially when designing and improving complex processes with multiple conflicting objectives. This paper presents the mutual benefits that are gained when combining lean, simulation and optimization and how they overcome each other´s limitations. A framework including the three concepts, some of the barriers for its implementation and a real-world industrial example are also described.
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| 9. |
- Goienetxea Uriarte, Ainhoa, 1983-, et al.
(author)
-
Lean, simulation and optimization : A maturity model
- 2017
-
In: IEEE International Conference on Industrial Engineering and Engineering Management. - : IEEE. - 9781538609484 - 9781538609477 - 9781538609491 ; , s. 1310-1315
-
Conference paper (peer-reviewed)abstract
- This article presents a maturity model that can be applied to support organizations in identifying their current state and guiding their further development with regard to lean, simulation and optimization. The paper identifies and describes different maturity levels and offers guidelines that explain how organizations can grow from lower to higher levels of maturity. In addition, it attempts to provide the starting point for organizations that have applied lean or are willing to implement it and which may also be considering taking decisions in a more efficient way via simulation and optimization.
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| 10. |
- Goienetxea Uriarte, Ainhoa, 1983-, et al.
(author)
-
Supporting the lean journey with simulation and optimization in the context of Industry 4.0
- 2018
-
In: Procedia Manufacturing. - : Elsevier. - 2351-9789. ; 25, s. 586-593
-
Journal article (peer-reviewed)abstract
- The new industrial revolution brings important changes to organizations that will need to adapt their machines, systems and employees’ competences to sustain their business in a highly competitive market. Management philosophies such as lean will also need to adapt to the improvement possibilities that Industry 4.0 brings. This paper presents a review on the role of lean and simulation in the context of Industry 4.0. Additionally, the paper presents a conceptual framework where simulation and optimization will make the lean approach more efficient, speeding up system improvements and reconfiguration, by means of an enhanced decision-making process and supported organizational learning.
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