Quantifying Transparency in Production Logistics: An Improved Process Modelling Technique for Supporting Digital Transformation

The geomorphology teaching, which involves concepts about complex physical-natural processes, has traditionally adopted an approach based on methodologies of expository lessons aided by field excursions. However, the educational practices in modern society require the utilization of innovative technological resources subsidizing the learning process. Additionally, there is a growing demand for the inclusion of students with special educational needs (e.g. low vision and blinds) in different educational contexts. In view of this and considering the recent methodological advances in scientific research in Geomorphology with the use of geotechnologies, this work applied Virtual Reality and 3D digital and physical models’ resources in education, aiming at shortening the distances between theory and practice. Through photogrammetry and digital modeling using the Structure from Motion algorithm and gamification in Virtual reality, it is possible to simulate, in an immersive environment, a multissensorial and practical experience, reproducing the fieldwork virtually. This was carried out by the computational reproduction of real scenarios, such as caves, inselbergs, canyons, and coastal cliffs. The digital and physical 3D models of these landforms were thus used in teaching activities in basic education (Middle and High School), with the objective to promote an interactive and inclusive pedagogical practice, contemplating the National Digital Education Policy in Brazil.

Comparison of automated grading of digital orthodontic models and hand grading of 3-dimensionally printed models.

The food processing industry is one of the most complex manufacturing environments in terms of decision-making, production scheduling, and maintaining food safety [1]. Each market often demands unique product formulations, which leads to frequent changeovers and cleaning cycles to stay compliant and preserve product integrity [1]. These transitions can significantly impact operational efficiency — in fact, some large-scale plants experience 25–30% OEE losses solely due to cleaning and changeover activities. As product variety increases, so does the complexity of scheduling. Managing this manually can quickly become overwhelming — humans simply cannot evaluate every possible combination or scenario within a large-scale production environment [1]. Inefficient scheduling not only leads to production delays but also wastes resources and reduces throughput. This is where digital simulation and intelligent optimization models can make a substantial difference [1]. By simulating hundreds of potential production sequences, these models identify the most efficient plan, minimizing human error while maintaining compliance and productivity [1]. To achieve this, such systems must consider multiple interdependent factors, including: Market demand and customer-driven priorities, Material availability and supply variability, Operational efficiency, by minimizing cleans while ensuring product safety and regulatory compliance [1]. Beyond scheduling, maintaining food quality and safety is equally crucial — not just for consumer protection but also for public health and economic stability [2]. Traditional methods of food quality assessment, while effective, are often labor-intensive, destructive, and lack transparency or traceability [2]. Recent advancements in deep learning and computer vision now offer digitally intelligent, automated, and cost-effective solutions that enhance the precision, consistency, and speed of food quality monitoring [2]. As reviewed in the study [2], these technologies follow a typical workflow — beginning with data acquisition and preprocessing, followed by model selection, training, and validation. They are increasingly applied across various domains, such as image classification, object detection, image segmentation, and image generation [2]. Moreover, integrating these systems with the Internet of Things (IoT) and digital twin frameworks enables real-time monitoring, predictive maintenance, and proactive control of food processing operations [2]. The broader framework for such digital integration can be visualized through five interconnected modeling layers, linking consumer behavior and production dynamics [1]. Consumer preferences are represented at the sensory and sales levels, while production performance is modeled at the phenomena, unit-operation, and plant levels [1]. Together, these create a unified multi-scale model that connects what customers desire with how factories manufacture — ensuring a smooth flow of information and decisions across both domains [1]. Practical examples such as cream cheese fermentation and meat freezing demonstrate how these multi-layered models can guide decision-making in real industrial contexts as shown in the study [1]. While challenges remain in collecting and synchronizing data across different scales, the integration of simulation, IoT, and deep learning technologies shows tremendous potential to drive economic efficiency, food safety, and sustainable growth within the food processing industry [1,2]. This review contributes by establishing a structured framework that integrates digital twin modeling with intelligent scheduling to enhance decision- making, production efficiency, and food safety in a very complex environment. The proposed integration lays the framework across the industry hence therefore it bridges cognitive scheduling approaches and digital twin frameworks, highlighting how human decision-making and digital modeling can be integrated to improve production reliability, reduce changeovers, and support data-driven operations in complex food processing environments.

With the rise of the digital in architecture and the availability of digital fabrication tools, the interest in the material aspect of the model has intensified. At the same time, the design space for exploration of material behavior and its design potential has been extended from the physical into the digital. This has resulted in a cyclic set of translations from the physical realm into the digital by means of mathematical descriptions and back from the digital realm into the physical by means of digitally controlled fabrication processes. Despite the availability of more and more computational power and improvement of precision in simulation, these translations from the physical into the digital and vice versa can never be exact (Eco 2006), the translations from the physical model into a digital model and from the digital into the physical are spaces of (Evans 2000). The current paper explores in more detail this space of instability between physical and digital models, its potential for architectural design, and the central role of the mathematical description in this reciprocal set of translations.

Aim: Coopetition, as a way to increase the operational efficiency of business operations, is an attractive but high-risk strategy. The aim of the study was to demonstrate that logistics enterprises undertaking competitive cooperation related to the supply chain in the area of supply and production logistics, while increasing their competitive advantage, are at the same time exposed to a greater risk of losing strategic resources. Methodology: Risk in this context means that despite the effective management of logistics processes within the framework of coopetition between enterprises, there may be circumstances related to the risk of cooperation which will make it difficult to achieve results in the area of enterprise logistics in coopetition relations. Regarding the acquisition of information, qualitative research was used, based on the knowledge of experts and employees involved in logistics processes as part of coopetition between the surveyed logistics enterprises, especially in the area of supply and production processes. Results: This article presents the results of research into the risks in the area of logistics processes for selected 49 companies belonging to the TSL (transport, shipping, logistics) sector out of a research group of 223 companies belonging to various sectors, including information technology, transport, production, finance, cooperating within competitive ties. The outcome of the undertaken research is the identification of significant threats related to competitive cooperation between enterprises, which has a significant impact on logistics activities and processes which ensure the assumed effects of this cooperation. The study allowed to determine the risks that exist in the competitive cooperation processes in the surveyed enterprises. Implications and recommendations: The conducted research related to the identification of risks of competitive cooperation has a practical dimension, because by identifying them we have a picture of threats to competitive cooperation. Secondly, before making a decision on competitive cooperation, this risk should be estimated and the right decision should be made. Originality/value: The article provides valuable guidelines useful for business practice in the form of a classification of the sources of risk occurring in the process of coopetitioning between enterprises at different stages of cooperation, considered in different cross-sections (object of exchange, number of entities, degree of formalisation of cooperation, intensity of relations). These findings should help avoid problematic situations in the coopetitive relation.

The field of managing the logistics of agricultural products under significant dynamic changes in today's conditions requires the formation of new approaches using the possibilities of modern information tools. The article presents a systematic mathematical approach to logistics management in agriculture for conditions with an insignificant level of risk and under conditions of significant threats to the logistics processes of the agricultural industry. The presented study also examines the issue of analyzing the effectiveness of management actions in the logistics process, both operationally and strategically.The developed mathematical approach takes into account a wide range of conditions for carrying out logistics activities - both at a low level of risk in the implementation of the logistics process, and in circumstances of significant threats that lead to the minimization of the reliability of logistics in the agricultural sector. This is especially important today, given the significant level of negative impacts on logistics processes due to military threats. The growth of these influences even leads to the destabilization of the world food market, and the threat of famine in some regions of the world.The proposed mathematical approach takes into account both the emergence of new risks, the significantly increased dynamic nature of the effects on logistics activities in the agricultural sector of the economy, and the traditional specificity of the conditions for the implementation of logistics processes in the agricultural sector. The specificity of logistics management in the agricultural sector is due to the peculiarities of the agricultural production process; properties inherent in agricultural products, conditions of distribution of these products. This determines a wide range of tasks that must be performed by the logistics of the agricultural sector. This, in turn, creates a need for a highly adaptive dynamic approach when forming a set and combination of logistics tasks and goals. Algorithms, tools and methods were specially developed to implement this approach. In particular: the unification of target functions; the approach of flexible adaptive changes in the ranks of target functions to ensure the appropriate level of rationality of logistics process management; a compromise approach in the case of the need to simultaneously achieve a group of set goals or a group of goals; the approach of assessing the strategic impact of a management decision for operating not with static values of parameters, but with their trends over time. In general, this makes it possible to achieve the appropriate level of economic efficiency of agricultural logistics management even with dynamic changes in the conditions of its implementation and to ensure a high level of reliability of the logistics process even with an increase in the level of threats.

This paper questions whether physical and digital models can be seen as models for rather than models of architecture. Stressing the mediated nature of the design process, it questions the role models play in the early stage of architectural design. This research draws from an experimental digital & physical modelling workshop. The conclusion argues for a modelling process that incorporates both physical and digital modelling, and acknowledges the mediated nature of the design process.

The proliferation of online and digital data in our world yields unprecedented opportunities for connecting physical and digital parametric models with live data input and feedback. Tangible interfaces and augmented displays provide theatrical settings for designers to visualize real-world data and experience realtime feedback while manipulating physical and digital models on the table. This paper proposes a new approach to design workflow, where physical model and virtual model can be interconnected and informed in realtime by multiple analytical datasets and live data streams. Using 3D scanning, blob detection, and multi-touch techniques, multidimensional tangible interfaces and augmented displays presented in this paper demonstrate a powerful new approach for designing and interacting with physical models, materials, and environmental data.

In modern economic conditions, the management of transport and logistics flows is associated with the universal penetration of digital technologies. Digitalization allows for the optimization of the entire supply chain, including transportation and warehousing operations. Digital technologies provide opportunities to increase the economic efficiency of business processes in logistics, improve the safety and quality of transport and logistics flow management, and enhance the competitiveness of entities in transport and logistics systems. This article presents the research results of the mechanism for the digital transformation development of transport and logistics activities. The developed mechanism includes the process of automation and informatization of business processes; the process of combining various information technologies; the process of creating a model reflecting data online; the process of deciphering the received data; the process of compiling forecast data, as well as the process of editing the system without human intervention. The ultimate goals of developing this mechanism may be the creation of a digital product development system, the formation of a digital platform for integration into a flexible network, the creation of a digital transformation ecosystem, the implementation of flexible and integrated supply chain management, the development of a KPI system and evaluation of the effectiveness of transport and logistics activities, the selection and hiring of qualified personnel, the creation of an integrated information system and cloud data storage; as well as the implementation of electronic document management and a digital modeling and forecasting system. The comprehensive development and transformation of transport and logistics systems through their digitalization will ensure such potential results as the transition to new business models for the functioning of systems, flexible communication channels in the process of performing transport operations, as well as to products and business processes that are based on fundamentally new approaches to information management using digital technologies, and, as a result, to a significant increase in the efficiency of transport and logistics systems and their long-term sustainability.

In the field of orthodontics, digital dental arch models are increasingly replacing plaster models in orthodontic diagnostics. This change in interface from physical plaster models to digital image-based models raises the question of how orthodontists interpret intra- and inter-arch relationships from an image on a screen. In particular, the issue of the accuracy of the distances estimated on numerical models is crucial since the estimation of distances is the basis of the therapeutic decision-making process. Studies have shown that distances were well estimated on plaster models, but no study has verified this point on numerical models. This is the question that our study addresses. The experimental protocol consisted of collecting estimates of measurements made by orthodontists using digital models. The reliability of these measurements was then assessed by comparing them to the actual physical distances. We asked 31 orthodontists (19 women and 12 men; an average age of 37 years) to generate 3D model-based measurements of seven different elements: mandibular congestion, the maxillary intermolar distance, Spee’s curve, 16/26 symmetry, the right canine class, overbite, and overjet. These values were then compared to the actual measurements calculated using Insignia® software (ORMCO Corporation: Brea, CA, USA), using single sample t-tests. This test makes it possible to compare a distance estimated by the participants with a reference value, which corresponds here to the real distance. The results indicate that, overall, the distance estimates made on the 3D models differ significantly from the actual distances measured using the Insignia® software. This was particularly so for mandibular crowding (test value = 0; t (30) = 10.74; p ≤ 0.01), test value = 1; t (30) = 6.23; p ≤ 0.01). Although no study has focused on distance estimation on numerical models in the field of orthodontics, our results agree with the conclusions of studies showing that distances are not estimated in the same way in real environments and virtual environments. Additional studies will make it possible to identify more clearly the parameters (individual factors, equipment, etc.), which make it possible to improve the estimation of distances in the practice of orthodontics. In any case, these studies are necessary to improve the training of future practitioners in the use of virtual models for decision-making and to support them in the digital transition.

The combined use of digital and physical models promotes inclusive communication and represents an important medium for presenting heritage to the community, particularly to the tourism sector. The work presented here concerns the Grand Staircase of the Birago di Borgaro Palace in Turin, designed by Filippo Juvarra and built from 1716 onwards. The monumental staircase is located near the main atrium; its development takes place on three right-handed ramps leading to the main floor hall. The contribution focuses on the application of digital technologies for three-dimensional modelling and digital fabrication, aimed at studying and communicating the constructive aspects of architectural heritage. The adopted methodology involves the use of data from previous acquisitions and restitutions (TLS survey by Prof. M. C. López González, two-dimensional drawing by Arch. F. Natta) for the digital modelling of the Grand Staircase in order to retrace the formal ideation process related to the applied construction techniques. Starting from the virtual model, through digital fabrication techniques, a physical model is created on a 1:50 scale, composed of four main blocks obtained using three vertical section planes. The model, in addition to restoring the compositional apparatus of the decorations, aims to make understandable, explicit and readable the construction system used in the design: on the one hand, it restores the overall three-dimensional morphology of the artefact, and on the other, it offers the possibility to be explored revealing the structural composition through the constituent elements such as the ramping barrel vaults, the cross vaults that support the landings and the stiffening arches. The physical model of the Grand Staircase of the Birago di Borgaro Palace is an example of how the physical representation of the built space can become an expression of layered and sedimented information, lending itself to the communication of knowledge even to a non-expert audience.

Nowadays mapping urban spaces is becoming easier and more accessible because it can be implemented with the use of modern Internet tools. Most maps and data are shared online and can be shown in flat, two-dimensional (2D) drawings as plans. Some spatial data and information relate to the physical structure of a city, including city morphology, which is best represented in the form of a three-dimensional (3D) model. The chapter presents experiences related to the use of mapping in the analysis of the urban structure of cities. The conclusions from the research carried out cyclically in multiperson groups in the project-based learning (PBL) formula in 2018, 2019, and 2020 are presented. The research was devoted to the analysis of the structure of cities, including public spaces: Metropolis GMZ (pl. Górnośląsko-Zagłębiowska Metropolia – the Metropolitan Association of Upper Silesia and Dąbrowa Basin), Bologna and Aachen. The mapping effects were presented as physical, digital, or augmented reality models. This form of presentation is not typical and turned out to be useful in education in the field of architecture and urban planning. The experiences with physical models expressing the structure of cities and representing the data show that the method is useful in a typical stationary didactic process. The experiences with digital models and augmented reality show that this technology can be very useful in remote learning.

The aim of the article was to develop a model for managing logistics processes in the supply chain. The use of process analysis and integration of logistics processes in the supply chain enabled the continuity of power in the process of supply and in the production process and it also enables the effective and efficient distribution process management. Basing on the developed map of logistics processes author of the article described the place in the process where one can apply optimization methods of quantity and quality. By using statistical quality control it was possible to shorten the duration of the adoption process of delivery to the warehouse, thereby lowering the cost of quality control. Integration of supply processes and production logistics in the supply chain enabled the continuity of power of parts in the production process, however thanks to the combination of methods DRP (Distribution Requirements Planning), Kanban, VMI (Vendor Managed Inventory) and CPFR (Collaborative Planning, Forecasting and Replenishment) we obtain the effective and efficient distribution process management.

(1) Background: Industry 4.0 and the COVID-19 pandemic have resulted in an acceleration of digital transformation, primarily in production systems and logistics. This raises the need to assess where a company is in its digital transformation today and what measures must be taken to improve logistics processes. This article aims to present the results of a study assessing the digital maturity of logistics processes in a group of selected enterprises located in Poland. The research was conducted among companies that are business partners of the Poznan School of Logistics. (2) Methods: The DMM-OP digital process maturity assessment model was used in the study. Digital maturity was assessed on a five-point scale in four areas of company activity: process management, performance measurement, employee support, and technology. The research procedure included four stages. (3) Results: The results indicate that companies in the process management and performance measurement dimensions achieved the highest level of digital maturity. In commercial enterprises, the level of digital transformation is at the lowest level. Large enterprises achieved the best results, but there were also very good results in the group of small enterprises. (4) Conclusions: The results presented in the article can be used by industry and academia. The research was not statistical but can form the basis for benchmarking analyses.

Internet of things technology is the basis of transformation and upgrading of manufacturing industry and it is also the basis of realization of intelligent manufacturing. The introduction of Internet of things technology in the production workshop can promote the transformation of manufacturing and logistics business models, as well as collaborative production scheduling and logistics scheduling. This paper discusses the goal setting of intelligent workshop production logistics system, the structure of intelligent workshop production logistics system and the key technologies to be solved in constructing intelligent workshop production logistics system. On this basis, the paper analyzes the characteristics of production logistics of tire enterprises, puts forward the train of thought of constructing intelligent production logistics system in rubber refining workshop, component workshop, molding workshop and vulcanization workshop of tire enterprises, and finally analyzes the expected effect. Intelligent workshop production logistics system can realize the integration of intelligent manufacturing and intelligent logistics, improve the production efficiency and logistics efficiency of manufacturing enterprises.