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Abstract: The Stage-Gate® model has historically provided a systematic framework for New Product Development (NPD). However, the evolving landscape of innovation necessitates continuous enhancement. This paper redefines the model's foundational structure by advocating for the recognition of the Discovery Phase as Stage 1, emphasizing its essential role in aligning initial ideation with strategic goals, streamlining processes, and enhancing NPD efforts. Using a mixed-methods approach, including a systematic literature review, synthesis of illustrative examples and secondary data and case study analysis, the research demonstrates that formalizing the Discovery Phase improves earlystage decision-making, enhances alignment between front-end exploration and downstream execution and mitigates risks by supporting more informed project development. Synthesised sectoral examples show that incorporating the Discovery Phase improves feasibility, reduces risk, and boosts efficiency. For example, simulation planning early in innovation process increased manufacturing throughput by 52 %, while early IP checks lowered infringement risk. The proposed revision boosts the Stage-Gate® model's adaptability and integration with modern methodologies such as AI, Agile, Lean Startup, Design Thinking and TRIZ. The findings highlight how this change promotes a comprehensive approach to NPD. The implications extend to practical applications and future research, offering organizations a flexible framework that meets modern market and technological demands.
Keywords: Stage-Gate® model, fuzzy front end of innovation (FFEI), new product development (NPD), innovation management, discovery phase, agile, TRIZ, design thinking, large language model (LLM), sustainability
Published in DKUM: 03.11.2025; Views: 0; Downloads: 7
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Abstract: This article presents a cloud-based system for the on-line monitoring of tool conditions in end milling. The novelty of this research is the developed system that connects the IoT (Internet of Things) platform for the monitoring of tool conditions in the cloud to the machine tool and optical system for the detection of cutting chip size. The optical system takes care of the acquisition and transfer of signals regarding chip size to the IoT application, where they are used as an indicator for the determination of tool conditions. In addition, the novelty of the presented approach is in the artificial intelligence integrated into the platform, which monitors a tool’s condition through identification of the current cutting force trend and protects the tool against excessive loading by correcting process parameters. The practical significance of the research is that it is a new system for fast tool condition monitoring, which ensures savings, reduces investment costs due to the use of a more cost-effective sensor, improves machining efficiency and allows remote process monitoring on mobile devices. A machining test was performed to verify the feasibility of the monitoring system. The results show that the developed system with an ANN (artificial neural network) for the recognition of cutting force patterns successfully detects tool damage and stops the process within 35 ms. This article reports a classification accuracy of 85.3% using an ANN with no error in the identification of tool breakage, which verifies the effectiveness and practicality of the approach.
Keywords: machining, end milling, tool condition monitoring, chip size detection, cutting force trend identification, visual sensor monitoring, cloud manufacturing technologies
Published in DKUM: 26.03.2025; Views: 0; Downloads: 10
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Abstract: Because of the prevalence of depression, its often-chronic course, relapse and associated disability, early detection and non-intrusive monitoring is a crucial tool for timely diagnosis and treatment, remission of depression and prevention of relapse. In this way, its impact on quality of life and well-being can be limited. Current attempts to use artificial intelligence for the early classification of depression are mostly data-driven and thus non-transparent and lack effective means to deal with uncertainties. Therefore, in this paper, we propose an end-to-end framework for extracting observable depression cues from diary recordings. Furthermore, we also explore its feasibility for automatic detection of depression symptoms using observable behavioural cues. The proposed end-to-end framework for extracting depression was used to evaluate 28 video recordings from the Symptom Media dataset and 27 recordings from the DAIC-WOZ dataset. We compared the presence of the extracted features between recordings of individuals with and without a depressive disorder. We identified several cues consistent with previous studies in terms of their differentiation between individuals with and without depressive disorder across both datasets among language (i.e., use of negatively valanced words, use of first-person singular pronouns, some features of language complexity, explicit mentions of treatment for depression), speech (i.e., monotonous speech, voiced speech and pauses, speaking rate, low articulation rate), and facial cues (i.e., rotational energy of head movements). The nature/context of the discourse, the impact of other disorders and physical/psychological stress, and the quality and resolution of the recordings all play an important role in matching the digital features to the relevant background. In this way, the work presented in this paper provides a novel approach to extracting a wide range of cues relevant to the classification of depression and opens up new opportunities for further research.
Keywords: digital biomarkers of depression, facial cues, speech cues, language cues, deep learning, end-to-end pipeline, artificial intelligence
Published in DKUM: 17.01.2025; Views: 0; Downloads: 14
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Abstract: Single photon sensitive detectors used in high energy physics are, in some applica-tions, required to cover areas the size of several m2, and more specifically in very strong demand with an ever finer imaging and timing capability for Cherenkov Ring Imaging Detector (RICH) configurations. We are evaluating the Large Area Picosecond Photo-detector (LAPPD) produced by INCOM company, as a possible candidate for future RICH detector upgrades. In this work we perform tests on the second generation device, which is capacitively coupled to a custom designed anode back plane, consisting of various pixels and strips varying in size, that allows for connecting various readout systems such as standard laboratory equipment, as well as the TOFPET2 ASIC from PETsys company. Our aim is to evaluate what can be achieved by merging currently available technology, in order to find directions for future developments adapted for specific uses.
Keywords: data acquisition circuits, data acquisition concept, front-end electronics for detector readou, digital electronic circuits
Published in DKUM: 06.02.2024; Views: 278; Downloads: 34
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Abstract: Magical realism as a literary mode has been the cause of numerous debates since the publication of One Hundred Years of Solitude by the Colombian author Gabriel García Márquez in 1967, which the majority of critics consider to be the first magical realist novel. Magical realism has been frequently confused with fantasy and is still considered by some as the latter’s branch. Though there is no unified definition of magical realism, critics have agreed upon some of the most common characteristics. The present thesis makes use of Wendy B. Faris’s theoretical framework on the mode’s characteristics and applies it to A Monster Calls by Patrick Ness and The Ocean at the End of the Lane by Neil Gaiman. In both novels, marvellous happenings are incorporated seamlessly into a realistic narrative, which is the basic definition of magical realism. The events are presented matter-of-factly; thus, readers perceive them as realistic. Both novels also contain the primary characteristics that define magical realism as a literary mode, according to Faris. A Monster Calls has been adapted into a movie as well as translated into Slovene as Sedem minut čez polnoč. In the translation, magical realism retains its characteristics, since it is mainly a content based literary mode. In the movie, however, visual representations of the irreducible element, i.e. the yew tree monster, offer the viewers an opportunity to perceive it as ordinary.
Keywords: magical realism, A Monster Calls, The Ocean at the End of the Lane, Sedem minut čez polnoč
Published in DKUM: 28.09.2018; Views: 2071; Downloads: 245
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