Design Methodology and Tools in Factory of the Future

This paper presents a design method and tool developed to support the skill forming activities in the DigiFoF network (https://www.digifof.eu/). The focus is on training of manufacturing system design skills both as HEI education and vocational training, but preliminary design of new manufacturing systems is also supported (e.g in the development of small business process scenarios). We proposed a model-based methodology for solving of the manufacturing system design problems The methodology and the supporting tool are centred around a less abstract Domain-Specific Modelling Language (DSML). The language is easy to learn due to its few components. A modelling and simulation environment named Digital Production Planner Tool (DPPT) was generated from the metamodel of the DSML. The degree of abstraction used by this tool corresponds well to the intended use in training and preliminary design. Our method incorporates by design the possibility to impose constraints at the modelling language level to limit the modelling space to feasible/possible solutions. The resulting tool enforces these constraints in the use and supports the development of feasible designs even by inexperienced designers. The access to the conceptual model allows the translation of the model to other modelling language like Petri net. This extends the support for the design methodology. The whitepaper presents a use case for the developed method and tool: the design of a chocolate manufacturing line.

The Future of Factories: Different Trends

The technological advancements promote the rise of the fourth industrial revolution, where key terms are efficiency, innovation, and enterprises’ digitalization. Market globalization, product mass customization, and more complex products need to reflect on changing the actual design methods and developing business processes and methodologies that have to be data-driven, AI-assisted, smart, and service-oriented. Therefore, there is a great interest in experimenting with emerging technologies and evaluating how they impact the actual business processes. This paper reports a comparison among the major trends in the digitalization of a Factory of the Future, in conjunction with the two major strategic programs of Industry 4.0 and China 2025. We have focused on these two programs because we have had experience with them in the context of the FIRST H2020 project. European industrialists identify the radical change in the traditional manufacturing production process as the rise of Industry 4.0. Conversely, China mainland launched its strategic plan in China 2025 to promote smart manufacturing to digitalize traditional manufacturing processes. The main contribution of this review paper is to report about a study, conducted and part of the aforementioned FIRST project, which aimed to investigate major trends in applying for both programs in terms of technologies and their applications for the factory’s digitalization. In particular, our analysis consists of the comparison between Digital Factory, Virtual Factory, Smart Manufacturing, and Cloud Manufacturing. We analyzed their essential characteristics, the operational boundaries, the employed technologies, and the interoperability offered at each factory level for each paradigm. Based on this analysis, we report the building blocks in terms of essential technologies required to develop the next generation of a factory of the future, as well as some of the interoperability challenges at a different scale, for enabling inter-factories communications between heterogeneous entities.

Flexible Robotic Assembly Based on Ontological Representation of Tasks, Skills, and Resources

Technology has sufficiently matured to enable, in principle, flexible and autonomous robotic assembly systems. However, in practice, it requires making all the relevant (implicit) knowledge that system engineers and workers have – about products to be assembled, tasks to be performed, as well as robots and their skills – available to the system explicitly. Only then can the planning and execution components of a robotic assembly pipeline communicate with each other in the same language and solve tasks autonomously without human intervention. This is why we have developed the Factory of the Future (FoF) ontology. At its core, this ontology models the tasks that are necessary to assemble a product and the robotic skills that can be employed to complete said tasks. The FoF ontology is based on existing standards. We started with theoretical considerations and iteratively adapted it based on practical experience gained from incorporating more and more components required for automated planning and assembly. Furthermore, we propose tools to extend the ontology for specific scenarios with knowledge about parts, robots, tools, and skills from various sources. The resulting scenario ontology serves us as world model for the robotic systems and other components of the assembly process. A central runtime interface to this world model provides fast and easy access to the knowledge during execution. In this work, we also show the integration of a graphical user front-end, an assembly planner, a workspace reconfigurator, and more components of the assembly pipeline that all communicate with the help of the FoF ontology. Overall, our integration of the FoF ontology with the other components of a robotic assembly pipeline shows that using an ontology is a practical method to establish a common language and understanding between the involved components.

AWARENESS AS AN IMPORTANT COMPONENT OF THE ARCHITECTURE OF THE FACTORIES OF THE FUTURE

The article defines the Factory of the Future as a modern organizational concept of production and as a new type of industrial architecture. The concept of awareness as an important property of the architectural environment of the newest production facilities is disclosed. The main methods of its formation are listed and described. Examples of manufacturing facilities implementing awareness in its architecture are given. The conclusions about the positive impact of the awareness on the functioning of high-tech production facilities and Factories of the Future are made.

The beet sugar factory of the future

The beet sugar industry is facing several challenges for the future. The climate change is requiring a transition from the traditional fossil fuel to a greenhouse gas neutral energy source. The available possibilities for this purpose will be outlined in this paper. The recent EU sugar market reform has markedly increased the competition between sugar companies and the resulting lower sugar price has a significant impact on the profit margin of sugar production. In order to keep up with these challenges it is key to make an appropriate use of the available opportunities to improve the cost-efficiency of sugar beet processing. The different means to advance the sugar business are better asset utilization, continuous process improvement, introducing innovative process technologies and further developing a sugar factory into a biorefinery with a further valorisation of (co-)products and wherein synergy is obtained between different on-site process operations. Why and how these different available tools can improve the competitiveness of sugar factories will be discussed in detail. A proper combination and choice of the suggested changes and opportunities will enable sugar factories to get prepared for the future.

Multiple Sound Sensors And Fusion In Modern CNN-Based Machine State Prediction

In the new era of manufacturing with Industry 4.0, Smart Manufacturing (SM) is growing in popularity as a potential for the factory of the future. A critical component of SM is effective machine monitoring. Legacy machines indirect monitoring using Internet of Things (IoT) sensors are preferred instead of modifying hardware directly. Machine tools are composed of rotary components, resulting in machine tools emitting acoustic and vibratory signals. However, sound data cannot easily function as a direct representation for machine status due to its noise, variable time course, and irregular sampling. In this paper, we attempt to bridge this gap through machine learning techniques and auditory monitoring of auxiliary components (i.e., coolant, chip conveyor, and mist collector) as well as the main spindle running state of machine tools. Multi-label classification and Convolutional Neural Network (CNN) were utilized to train models for monitoring machine tools from the sound features. An external microphone and three internal sound sensors were attached to both mill and lathe machines. As a sound feature, Mel-frequency cepstrum (MFCC) features were extracted. The classification task performance was compared between each sensor location and early sensor fusion. The results showed that the sensor fusion approach resulted in the highest F1 score on both machine system.

PRINCIPLES OF DEPICTING REALITY IN MIKHAIL KONOVALOV's NOVELS

The article considers the novels "Vuryso Bum" ("Scarface", 1933) and "Gayan" ("Gayan", 1936) by Udmurt writer Mikhail Konovalov in terms of principles used by the author to create artistic reality. From the point of view of social realism, Mikhail Konovalov is free to experiment; he introduces constructivism, romanticism, naïvism using an arsenal of realistic devices; folklore and mythological origins are realised through a subconscious appeal to the Perm animal style ("Vuryso Bum") and a fairy tale model ("Gayan"). The prose writer reveals a regional spirit (animus loci); in his texts Ural is presented both as a spatial continuum and a living organism that determines characters’ personalities. For example, the novel "Gayan" depicts Izhevsk mining metallurgical settlement in the 1770s, the novel "Vuryso Bum" shows the working routine of Izhstal Plant rolling shop: one of the characters is dreaming about a factory of the future - a glass building immersed in trees, and people flying freely to colonised Mars. In the novel "Vuryso Bum", the main character is the collective "we" which combines many different personalities. The character of Gondyr, a trickster, existing between two worlds and trying to get used to an industrial city, can be considered the writer's artistic success. The "creator vs. destroyer" conflict, traditional for the 1930s, is embodied in the characters of a rational Dubov and a hidden enemy Nushin. An invariant of Beauty and the Beast's plot can be found in the relationship between Nushin and young Lina. The main principle of the novel "Gayan" is the combination of historical-ethnographic elements and elements of adventure. Varieties of fortunes of Gayan, a beautiful Luisa, and an ugly Balyan develop around a historical background of Pugachev's Rebellion; Emelyan Pugachev, Salavat Yulaev, Alymov, the head of Izhevsk Factory, and others play a certain role in their relationship. M. Konovalov creates a vivid and unique picture of ethnic reality in both novels.