Learning Factory Research Articles

Development of a hybrid teaching factory model based on school governance in improving employability skills of vocational students

This research aims to develop a framework for a hybrid teaching factory model that combines face-to-face and online learning with information and communication technology to improve employability skills in the new normal era. The research method uses the ADDIE Research and Development model, which consists of five stages: analysis, design, development, implementation, and evaluation. The research was conducted in several vocational high schools in DKI Jakarta Region, Indonesia. The findings in the research prove that the implementation of hybrid learning has an impact on students and teachers. Hybrid learning teaching factory is proven to be able to overcome frustrations and limitations between teachers and students in the learning process through online facilities, making teaching factory learning more innovative because there are variations of learning to interact and discuss, and making the classroom atmosphere conducive because students become happy and active in learning and skilled in working. The success of a hybrid teaching factory is considered mutually beneficial for both students and teachers who complete one of the teaching factory learning curriculums while industry instructors develop and work on collaborative platforms that provide useful services such as augmented reality and virtual reality-based applications.

The Quality of Implementation of Academic Supervision in Vocational Secondary Schools in Teaching Factory Based Learning

This research aimed to get an idea of how academic supervision activities are implemented in learning at SMK Negeri 2 Business and Management, Jayapura based on a teaching factory in the Marketing Department. The resource persons in this research were the school principal, teaching factory field coordinator teacher majoring in marketing, the deputy principal for the curriculum department, and female students majoring in marketing. The method used in this research is a descriptive qualitative approach, through observation, in-depth interviews, and documentation studies. The data obtained was analyzed using data reduction, data presentation, and conclusion. The results obtained from this research are that supervision activities have been carried out through class visits and work practice activities which have been carried out even though they have not been carried out on a scheduled basis and have only taken the form of monitoring. Apart from that, there is an assessment of student performance which the coordinator provides, there are efforts to develop learning programs by dividing block schedules and adjusting the curriculum according to industry needs, and there is feedback provided as input for improvements including transparency of profits from Esemkamart as well as monitoring of facilities and infrastructure, although there needs to be continuous improvement and more awareness regarding the implementation of occupational safety and health when carrying out the teaching factory learning process at SMK Negeri 2 Business and Management, Jayapura.

Process Analysis and Modelling of Operator Performance in Classical and Digitalized Assembly Workstations

Strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a lean learning factory was developed in the Pitesti University Center that allows students to learn about, experiment with, and research new lean manufacturing methods and techniques as well as Industry 4.0 in an environment similar to that of enterprises. The research presented in this study aimed to identify the minimum number of repetitions necessary to train operators to perform the same assembly operation while working at two differently organized workstations: one classic and the other including digital techniques. Several indicators were considered in our analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a lean-manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

Literature Review of The Development of a Green Campus Teaching Factory-Based Learning Model in Vocational Schools in Indonesia

This research is a literature review of the development of teaching and learning models in factories developed to create an education system capable of producing industry standard products or services. The literature review method is used in this article with references adapted to the research results. The discussion presented includes an analysis of vocational education about the basic philosophy of vocational education and the characteristics of vocational education, as well as models of administering vocational education. Furthermore, the development of the teaching factory learning model which includes Project-Based Learning (PBL) and Work-Based Learning (WBL) understands the context of its development. A study of the green campus-based teaching factory approach is then reported to determine the factors that influence it. In the final section, potential research and development related to the development of a teaching factory is presented to outline potential studies.

Analysis of "Productive and Educative" Performance in the Lesson Studies of the Center of Excellence SMK (Study at State Vocational High School 4 Bandar Lampung)

This research was carried out to determine the implementation of the teaching factory learning model and Project Base Learning in an effort to improve the productive and educational performance of grade XI students in specialization subjects at the State 4 Bandar Lampung vocational school. This research is qualitative research using data analysis techniques, namely Data Resolution, Data Presentation, Conclusion Drawing/Verification. The results of the Operational Research of the Education Unit by using the suitability of the Teaching Factory and PjBL planning models with the integration of the curriculum with each stakeholder and the appropriate assessment, the planning of the Teaching Factory and PjBL is able to improve Educational and Productive Performance. The Teaching Factory and PjBL models have a good contribution in improving the Educational and Productive Performance of Students in the Vocational School of Negeri 4 Bandar Lampung in the Department of Hospitality.

Design Model for the Digital Shadow of a Value Stream

The value stream method, a key tool in industry to analyze and visualize value streams in production, aims to holistically optimize process steps, reduce waste, and achieve continuous material flow. However, this method primarily relies on data from a single on-site inspection, which is subjective and represents just a snapshot of the process. This limitation can lead to uncertainty and potentially incorrect decisions, especially in industries producing customer-specific products. The increasing digitization in production offers a solution to this limitation by supporting the method through data provision. The concept of the digital shadow emerges as a key tool that systematically captures, processes, and integrates necessary data into a model to enhance traditional value stream mapping. This addresses the method’s shortcomings, especially in heterogeneous IT landscapes and complex value streams. To effectively implement the digital shadow this study identifies concepts of digital shadows and their key components and evaluates them for their relevance in industrial environments using an expert study. Based on the results, a design model is defined. This model entails guidelines to support companies with the practical implementation of the digital shadow of a value stream. Lastly, the model is evaluated on a realistic value stream in a learning factory.

Towards 5.0 skills acquisition for students in industrial engineering: the role of learning factories

In recent years, there has been an increasing transition towards the Industry 5.0 paradigm, which focuses on technology and sustainability but also on the resilience and human-centricity of the production and logistics processes. These changes require investment in equipment, process change, and new skills. To avoid the mismatch between the skills required by industry and the skills offered by university courses, recently, learning factories (LFs) have been spread worldwide, aiming at promoting hand-on learning approaches to manufacturing, logistics and technological processes. This paper illustrates how LFs can support the development of contents and competencies useful in the transition to Industry 5.0 in the industrial engineering courses. Starting from the description of a LF installed in Italy, this study presents a systematisation of the contents that can be addressed by adopting LF in the design of learning modules specifically facing the requirements and skills of the different Industry 5.0 areas.

Learning from strangers: transferability of current principles for designing inclusive area-based settlements to learning factories in resource-limited settings

What can we learn from the current design principles adopted to build inclusive area-based settlements such as refugee camps? How can we transfer the lesson learnt to useful principles for learning factories in resource-limited settings? Refugee camps are a form of settlement in which internally displaced persons (IDP)s reside and receive centralised protection, humanitarian assistance, and other services from governments and humanitarian actors. These settlements can be planned and developed on land allocated by the Government, or created spontaneously when persons of concern settle on land which has not been designated to accommodate them. This type of settlement often limits rights and freedom, such as the ability to move and work freely and they do not consider any sustainability insights. To overcome these limitations, it is necessary to pursue alternatives based on a separate set of design parameters that include life-cycle analysis. After analysing the current general situations of refugee camps and settlements, firstly, the paper offers a set of life-cycle principles to facilitate the achievement of long-term, sustainable, and inclusive temporary settlements and secondly a reflection on possible principles to transfer and apply to the design of learning factories in resource-limited settings.

Design and test of a Human-Machine Interface for assembly lines in a learning factory

Human-Machine Interfaces are pivotal in modern manufacturing, serving as the critical link between human operators and complex machinery. This paper explores the evolution of HMIs, emphasizing their importance in enhancing efficiency, safety, and productivity within manufacturing environments. While HMIs offer real-time monitoring and control functionalities, their effectiveness hinges on human-centric design principles. Incorporating insights from human-centred design, this research presents a case study conducted at the SLIM laboratory of the University of Bergamo. The study encompasses theoretical exploration, HMI re-design, and user evaluation within an automatic assembly line setting. The research identifies key factors influencing HMI usability through critical analysis and user feedback and offers valuable insights for optimizing HMIs and empowering operators in the digital manufacturing landscape.

Empowering Operator 5.0: human-centric design of an augmented reality tool for a learning factory

This study presents a human-centric design and prototype development of an Augmented Reality (AR)-based assistance tool aimed at supporting industrial maintenance technicians. Situated within the LEONARDO learning factory at the University of Calabria, the case study explores the potential of AR technology to prioritize the well-being, safety, and skill development of operators. Leveraging the 3I design thinking model, the study emphasizes the importance of inspiration, ideation, and implementation in developing effective AR solutions. Through user interviews and iterative design processes, the research identifies key insights into user preferences and learning styles, highlighting the need for practical, interactive educational methodologies. The resulting AR tool features intuitive guidance, task management support, safety reminders, troubleshooting assistance, training resources, and performance tracking functionalities, aligning with the principles of human-centric augmentation. The study underscores the significance of integrating human-centric values with technological advancements in fostering a proactive learning attitude among operators in smart manufacturing environments.

Assessing the Human Competence and Individual Support Level in Manual Assembly through Cognitive Assistance Systems

In today’s industrial landscape, production challenges arise from increasing demand for personalized products and demographic changes. Production facilities and employees must be agile and adaptable to changing requirements, while limited automation in multi-variant production elevates the importance of human workers. Cognitive assistance systems, such as digital instructions and pick-by-light systems, can enhance efficiency and reduce errors but should be customized to worker competence levels. This article presents a method for assessing worker competence and individual support using cognitive assistance systems in manual assembly, with an example from Fraunhofer IGCV’s "Learning factory for cyber-physical production systems" in Augsburg.

I4.0/5.0 MR training: Investigating MR tools to enhance learning experiences

As the manufacturing industry continues its shift towards highly complex Industry 4.0 production environments, there is an expected exponential increase and change in the demanded skills and qualifications among employees. However, traditional teaching methods may pose challenges when it comes to applying learned skills in real-life engineering situations, given the complexity of these environments. Recent advancements in technologies enabling virtual co-existence have opened up new opportunities for personalised and immersive services in pedagogy. While Mixed Reality (MR) and, more significantly, Metaverse infrastructure are still in their early stages, researchers and educators have the opportunity to lead the exploration of new avenues for reskilling educators and enhancing student learning experiences. This paper presents research conducted at the University of Malta, focusing on exploring the potential transformative pedagogical effects of MR in specialised Industry 4.0/5.0 engineering training. The paper proposes a framework for developing a Virtual Learning Factory (VLF) using MR technology, grounded in established and effective learning methodologies. The envisioned VLF aims to create an immersive experiential learning environment where engineering students can better adapt to the evolving industrial landscape, preparing them to excel in the dynamic era of advanced manufacturing. Additionally, the research delves into the potential impacts of MR-based training on enhancing training precision and efficiency.

A human-centric preference-based workforce dispatching with Machine Learning using the example of an assembly process

Human-centric in the context of Industry 5.0 aims to support and empower workers. This paper presents a human-centered approach to workforce dispatching. Thereby, workers’ preferences, skills, availability, and individual strain in the task are considered. To do this, the strain of the workers in the task is predicted using Machine Learning. In this way, the strain on the worker can be reduced by raising autonomy and production can be adapted to the worker’s needs. The practical implementation and evaluation are done in a logistics learning factory.

Investigating Learning Factories as a Learning Environment in Vocational Education and Training

Investigating Learning Factories as a Learning Environment in Vocational Education and Training

An Asset Administration Shell-Based Digital Product Passport as a Gaia-X Service

Within the context of the Sustainable Product Initiative of the EU, product passports will likely be required in more and more sectors. However, their introduction is associated with challenges considering data collection and technical implementation, as the degree of standardization and availability of technical implementations for product passports is still low. To address these challenges, this work presents a digital product passport using asset administration shells to enable standardized connectivity via REST interfaces and, thus, standardized information exchange. The data model created contains submodels that specify information concerning the entire lifecycle of the product. Furthermore, these data enable the determination of the carbon footprint of the products as well as remanufacturing. The product passport will be implemented as a Gaia-X service to enable a secure and decentralized collection, exchange, and storage of product related data. The developed digital product passport and the Gaia-X ecosystem will be set up as demonstrators in the Learning Factory Global Production.

Planning Assistant for Medium-term Capacity Management using Deep Reinforcement Learning

Industrial companies face challenges caused by volatile business environments. In particular, changing customer demands can have large impacts on their performance. Medium-term capacity management addresses this challenge by adapting the production capacity to the customer’s demand. This is usually done by experts or, in the best cases, supported by production planning software using linear programming or genetic algorithms.There is a growing trend for using production simulations or digital twins. These simulations can be coupled with demand forecasts and machine learning to create a planning assistant tool. This tool can support the operations manager to fnd the right set of measures to adapt the production capacity based on changing customer demand.In our work, we design such a planning assistant tool by using different algorithms, including deep reinforcement learning. We apply it in a learning factory for performance comparisons and can show promising results of deep reinforcement learning. Furthermore, we can show that this simple decision support system outperforms humans in the test setting.

Training on Improving the Implementation of Teaching Factory Learning at SMK Negeri Pagaralam

The «Free Schools» program was launched by the Indonesian government in 2020 to improve the quality of education in Indonesia. This program provides flexibility for schools in designing a curriculum tailored to student needs and potential. The objectives of this community service activity include realizing the vision and mission of the FKIP UPGRI Palembang Accounting Education Study Program, implementing the work program of the FKIP UPGRI Palembang Accounting Education Study Program, as well as providing knowledge and skills in education and financial management for students, teachers, education staff, and the like to face current developments. Learning can be an active process in which individuals construct their own knowledge through thought, experience, and interaction.

Exploring Learning Factory Transformations in Industry 5.0

Industry 5.0, an evolution beyond the technological advancements of Industry 4.0, emphasizes a human-centricity, sustainable, and resilient manufacturing paradigm. This shift necessitates addressing multifaceted challenges, including environmental sustainability, workforce skill gaps, human well-being, and implementation costs. Learning factories, conceived as a solution, bridge the gap between theory and practice by offering hands-on, experiential learning opportunities. However, current learning factories predominantly cater to Industry 4.0, lacking a focus on the human-centricity and sustainability crucial for Industry 5.0. This study explores the on-going transformations in learning factories and their potentials to address Industry 5.0 challenges.

Meta-model-based shop-floor digital twin architecture, modeling and application

Digital twin is regarded as the virtual counterpart of physical entities, which can mirror the physical behavior and performance. Digital twin technology provides strong support for the achievement of cyber-physical system and intelligent manufacturing. Many investigations have been carried out for the digital twin of specific products. However, there are less researches on digital twin in the shop-floor domain, and there is a lack of model-driven digital twin comprehensive architecture. The modeling approach to the full lifecycle of digital twin is not considered enough. This paper proposes a meta-model-based shop-floor digital twin construction approach and a comprehensive architecture. A meta-model based on RAMI 4.0 is constructed, which provide a novel idea for the description of manufacturing resources and their status. The proposed shop-floor digital twin architecture consists of three key implementation elements: the meta-model construction, data modeling (including data interaction between cyber-physical spaces) and constructing different integration level models of shop-floor digital twin based on iteration feedback between the demands and models. The proposed approach is validated through a case study of the fischer learning factory 4.0.

Action in the Business Realm: Increasing Students' Entrepreneurial Spirit Through Production Unit-Based Teaching Factory Learning

Purpose of the study: The aim of this research is to determine students' entrepreneurial spirit through production unit-based teaching factory learning.
 Methodology: The type of research used in this research is quantitative with a quasi-experimental type. The number of samples taken was 60 students consisting of 30 students in class VIII A and 30 students in class VIII B. The data collection technique used included distributing questionnaires. The data analysis technique used in this research is comparative analysis or T-test between class data that implements production unit-based Teaching Factory learning and those that do not.
 Main Findings: Based on the results of the T-test carried out, it was found that there was a difference in entrepreneurial spirit between the group who took part in learning at the teaching factory and the group who did not take part.
 Novelty/Originality of this study: The novelty of this research is that it explores the transformative potential of production unit-based Teaching Factory learning in fostering a dynamic entrepreneurial spirit among students in the business realm.