The transition from Industry 4.0 to Industry 5.0 requires a holistic approach. This includes balancing technological advancements with human and environmental considerations. The literature review in this paper identifies conditions and strategies for a successful transition. It highlights the importance of integrating advanced technologies like AI, IoT, and blockchain to leverage human creativity and problem-solving skills. The study examines barriers and enablers for this transition, including digital maturity and workforce upskilling. For a successful transition of supply chains to Industry 5.0, technological advancements must be integrated with circular economy models, cybersecurity, adaptability, and human and environmental considerations.

Karlstad Lean Factory (KLF) är en fullskalig simulatormiljö vilken är konstruerad och byggd för Lean Produktion träning av studenter och industrianställda. En praktisk workshop i KLF kommer att erbjudas som innehåller såväl “prova på” som diskussion och erfarenhetsutbyte

This paper describes the use of a flexible full-scale simulation environment for Lean Production training and education called 'KLF Karlstad Lean Factory'. Instead of using the PDCA cycle as model for improvement cycles, the authors have developed a model that is more descriptive; it supports training transfer to the work environment in a more intuitive way. Recently, the authors have started to use the simulator as a testbed for innovative production solutions. Together with a company, the simulator is configured so as to emulate their envisaged future production solution. This participatory modelling simulation process consists of three main stages: (i) creating a common view on aim and scope, (ii) configuration modelling, and (iii) simulations. After the simulations, participants tend to continue seeking improvements, which illustrates the effectiveness of the approach. Future work will include developing a model for measuring lean production maturity in SMEs.

 Models for continuous improvement processes and for game-based learning currently have some drawbacks. Based on work with Karlstad Lean Factory®, a dual model for game-based learning and improvement processes is presented. This model also shows instructional scaffolding, and there is evidence that its use stimulates training transfer. A natural step is to extend the use of fullscale lean production simulators to a novel use as innovation testbeds. This can lower the threshold for production innovation in SMEs. A small case study shows how this novel use can be organised, with several benefits for the company.

In Lean Production training and education, simulators are often used.These can take the form of for instance desktop games, computersimulations, or full-scale simulators. Many training participants perceivemodels for experiential learning and for continuous improvementprocesses as complex and abstract. Based on experiences from trainingsessions in a full-scale simulator Karlstad Lean Factory®, a unifiedmodelfor learning and improvementwork is presented. Thismodel stimulatestraining transfer and is perceived as intuitive. It also shows instructionalscaffolding as a learning method. Suggestions for future work includeinvestigating synergy with Smart Manufacturing and the use of LeanProduction simulators for innovative product realisation.

Production simulation games are increasingly popular for training students and industrial employees in Lean Production principles. They range from paper- or desktop-based games to full scale simulators and proper manufacturing machinery. This paper reports on experiences from using both desktop games and a full scale simulator. Desktop games are suitable when training people who already have a fair understanding of lean principles. Shop floor workers usually have difficulties in seeing analogies between desktop games and their work environment. For both students and industrial workers, training effects and immersion tend to be higher when using full scale simulators.

In Lean Production training and education, simulators are often used. These can take the form of for instance desktop games, computer simulations, or full-scale simulators. Most evidence of training transfer from the training environment to the work situation is anecdotal, and as such is assessment of training transfer a research gap. Experiences from training sessions in Karlstad Lean Factory^® are presented, including a combination with computer simulation. A unified model for learning and improvement work is presented. Some suggestions for future work include investigating synergy with Smart Manufacturing and/or innovative product realization.

Simulation for training lean manufacturing ranges from simple paper-based or LEGO®-based games to larger scale simulation environments, for instance push car assembly. Some models for game-based learning are discussed and a model for lean manufacturing training is adopted . Many types of simulation may be suitable for teaching some basic elements of Lean manufacturing to students, but they are often less suitable for training industry workers in applying Lean manufacturing in their work environment. The latter group is more used to intuitive learning than to formal instruction. Thus, it is important that a training environment for this group more realistically represents the work environment; otherwise training transfer will be limited. For this reason, a lean training environment that includes materials processing stations as well as assembly areas was created. The stations exhibit some realistic behaviour such as stochastic breakdowns. Based on a comparison between factory workers and university students, five hypotheses for testing in future work are proposed.

Both literature and manufacturing companies state that simulators for providing training in lean production to industrialemployees must be similar to the work environment. This motivated the design of Karlstad Lean Factory, which is a trainingenvironment that realistically resembles an industrial environment. It is a full-scale training facility that incorporates acombination of materials processing and assembly. Parameters such as processing times, breakdown intervals and repair typescan be set. Examples of basic and more advanced training scenarios are given. Experiences from training groups of industrialemployees are described; inhomogeneity of these groups requires some specific attention.

Simulation for training lean manufacturing ranges from simple paper-based or LEGO®-based games to larger scale simulation environments, for instance push car assembly. Whilst such simulations may be suitable for educating students, they are often less suitable for training industry workers. The latter group is more diverse and is more used to intuitive learning than to formal instruction. Thus, it is important that a training environment for this group more realistically represents the work environment; otherwise training transfer will be limited. For this reason, a lean training environment that includes materials processing stations as well as assembly areas was created. The stations exhibit some realistic behaviour such as stochastic breakdowns. Based on a comparison between factory workers and university students, hypotheses for testing in future work are proposed.