Virtual Prototyping: Evaluating the Digital Twin Based Virtual Factory for New Product Introduction

Shortening lifecycles and increasing complexity make product and production lifecycle processes more challenging than ever for manufacturing enterprises. Virtual Prototyping (VP) technologies promise a viable solution to handle such challenges in reducing time and physical builds as well as increasing quality. In previous studies, the Digital Twin (DT) based Virtual Factory (VF) concept showed significant potential to handle co-evolution by integrating 3D factory and product models with immersive and interactive 3D Virtual Reality (VR) simulation technology as well as real-time bidirectional data synchronisation between virtual and physical production systems. In this article, we present an extension to the paper “Demonstrating and Evaluating the Digital Twin Based Virtual Factory for Virtual Prototyping” presented at CARV2021. The study presents an evaluation by industry experts of the DT based VF concept for VP in the context of New Product Introduction (NPI) processes. The concept is demonstrated in two cases: wind turbine blade manufacturing and nacelle assembly operations at Vestas Wind Systems A/S. The study shows that the VF provides an immersive virtual environment, which allows the users to reduce the time needed for prototyping. The industry experts propose several business cases for the introduced solution and find that the phases that would have the most gain are the later ones (production) where the product design is more mature.

The "competence" concept in the educational system of European countries within a competence-oriented approach

The object of research is the concept of "competence" in the educational system of different countries. Investigated problem. Theoretical generalization of the concept of "competence" and the peculiarities of its formation in the process of professional training of applicants for higher education in European countries. Creation of a model of professional training for applicants for education of the first (bachelor's) level. Main scientific results. The definition of the concepts "competence" and "legal competence", which are most often used in pedagogical research, has been analyzed. The definition of "competence" within the competence-oriented approach is given. The competence-based approach in education is understood as training not just a specialist with a system of knowledge, but a high-level professional and a comprehensively developed personality. A model for the formation of legal competence of applicants for higher education has been created. Through the introduction of innovative methods into educational processes, the legal thinking of bachelors is developing. Legal competence presupposes a set of knowledge, skills, characteristics acquired by students in the learning process, necessary to perform certain actions in order to solve problems, tasks, situations in accordance with the prescriptions of the rule of law. The formation of a system of knowledge, abilities, skills, methods of activity in students in the learning process are significant. This requires both their psychological "restructuring" and the improvement of curricula and educational technologies. The traditional teaching of lectures and the conduct of seminars should be complemented by elective courses and special courses. The area of practical implementation of the research results. Formation of competencies in the process of professional training of applicants for higher education of the first (bachelor's) level in order to achieve programmatic learning outcomes, apply the acquired knowledge in future professional activities and everyday life. Innovative technological product. Creation of a training model for applicants for higher education based on a competence-oriented approach. Application area of an innovative technological product. Introduction of the educational model into the process of professional training of applicants for higher education of the first (bachelor's) level in order to promote the creation and strengthening of legal culture and creativity of students.

Diffusion Approximations for a Class of Sequential Experimentation Problems

A decision maker (DM) must choose an action in order to maximize a reward function that depends on the DM’s action as well as on an unknown parameter Θ. The DM can delay taking the action in order to experiment and gather additional information on Θ. We model the problem using a Bayesian sequential experimentation framework and use dynamic programming and diffusion-asymptotic analysis to solve it. For that, we consider environments in which the average number of experiments that is conducted per unit of time is large and the informativeness of each individual experiment is low. Under such regimes, we derive a diffusion approximation for the sequential experimentation problem, which provides a number of important insights about the nature of the problem and its solution. First, it reveals that the problems of (i) selecting the optimal sequence of experiments to use and (ii) deciding the optimal time when to stop experimenting decouple and can be solved independently. Second, it shows that an optimal experimentation policy is one that chooses the experiment that maximizes the instantaneous volatility of the belief process. Third, the diffusion approximation provides a more mathematically malleable formulation that we can solve in closed form and suggests efficient heuristics for the nonasympototic regime. Our solution method also shows that the complexity of the problem grows only quadratically with the cardinality of the set of actions from which the decision maker can choose. We illustrate our methodology and results using a concrete application in the context of assortment selection and new product introduction. Specifically, we study the problem of a seller who wants to select an optimal assortment of products to launch into the marketplace and is uncertain about consumers’ preferences. Motivated by emerging practices in e-commerce, we assume that the seller is able to use a crowd voting system to learn these preferences before a final assortment decision is made. In this context, we undertake an extensive numerical analysis to assess the value of learning and demonstrate the effectiveness and robustness of the heuristics derived from the diffusion approximation. This paper was accepted by Omar Besbes, revenue management and market analytics.

Pembentukan Persuasif Dalam Struktur Naratif Pada Iklan Gopay Indonesia Versi Bumbu Rahasia Dari Bu Sisca Yang Bikin #Lebihenak

The concept of an advertisement aimed at modern society can no longer rely solely on the description of a product. Because basically people can find their own info from a product using their smartphone. Therefore, an advertisement must be designed in such a way that it really attracts potential consumers. Persuasive messages need to be packaged well in order to achieve the target to influence consumers to use the company's products. The research "Pembentukan Persuasif Dalam Struktur Naratif Pada Iklan Gopay Indonesia Versi Bumbu Rahasia Dari Bu Sisca Yang Bikin #LebihEnak " aims to find a persuasive formation of a product advertisement used by modern society, namely Gopay Indonesia e-money through narrative analysis of one of the advertising versions, namely Bumbu Rahasia dari Bu Sisca yang Bikin #Lebihenak. The research method used is descriptive qualitative by collecting data through documentation, observation, and literature study. This research uses narrative theory from Bordwell-Thompson which sees the narrative elements consist of plot and story, space, time, characters, and narrative. The results showed that the formation of persuasion to grow awareness and product introduction was formed from each narrative element.

Markov Perfect Equilibria in Multi-Mode Differential Games with Endogenous Timing of Mode Transitions

We study Markov perfect equilibria (MPE) of two-player multi-mode differential games with controlled state dynamics, where one player controls the transition between modes. Different types of MPE are characterized distinguishing between delay equilibria, inducing for some initial conditions mode switches after a positive finite delay, and now or never equilibria, under which, depending on the initial condition, a mode switch occurs immediately or never. These results are applied to analyze the MPE of a game capturing the dynamic interaction between two incumbent firms among which one has to decide when to extend its product range by introducing a new product. The market appeal of the new product can be influenced over time by both firms through costly investments. Under a wide range of market introduction costs a now or never equilibrium coexists with a continuum of delay equilibria, each of them inducing a different time of product introduction.

ANALYSIS ON IMPOSITION OF SAFEGUARD MEASURE AND ADMINISTRATIVE SANCTION AGAINST TAX EVASION OF TEXTILES TAX AND TEXTILES PRODUCT IN INDONESIA

Import of textile product which keep getting higher has caused serious injury to the domestic textile industry, as an effort to protect domestic industry government has imposed additional import duty in form of safeguard duty for import of textile product. Introduction of safeguard duty is expected to give domestic industry an opportunity to adjust itself for competing with import product, but the establishment of safeguard duty for textile product is thought to be the trigger for tax evasion on import of textile product, against this violation government impose administrative sanction. The purpose of this research is to analyze the effect of safeguard duty imposition and administration sanction on tax evasion. Object of this research is all import activity on textiles product which has been imposed safeguard duty and committing administrative violation since the establishment of safeguard duty for textile product beginning on November 2019 till October 2020. Regression technique used is ordinary least square regression to regress cross section data. Research conclusion find that safeguard duty introduction significantly affecting tax evasion while administrative sanction didn’t have significant effect on reducing tax evasion.. Keywords: textile product, safeguard duty, administration sanction, tax evasion.

How Far the Digital Marketing Innovation done by Natural Raw Material MSMEs during the Pandemic? Case of Magelang Region, Central Java Region, Indonesia

There are various steps taken by Natural Raw Materials MSMEs in Magelang Region in facing the economic downturn during the pandemic for their business continuity. The effort to adapt to the difficulties during the pandemic period is by utilizing information technology to encourage the economy to continue growing and developing. The use of social media and e-commerce is an example of marketing adaptation from a traditional form to a more modern model. Participation in virtual exhibitions is also another example of how MSMEs adopt digital transformation. The study aims to determine how far the natural raw material MSMEs actors can utilize the digital marketing during the pandemic and prepare for the adaptation in the new normal period. This study uses a qualitative descriptive approach involving 30 MSMEs. The result shows that MSMEs who are transitioning away from traditional marketing techniques and attempting to be innovative in response to environmental changes have a chance to sustain themselves. Marketing via e-commerce, social media, and virtual product introduction can help to increase markets and enhance the economy. Those that are not prepared for the adaption process, on the other hand, will choose to operate other businesses or even close them.

A Bilingual Comparison of Sentiment and Topics for a Product Event on Twitter

Social media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and investigate which conversation topics arise during the time of a new product introduction on Twitter and how the overall sentiment is during and after the event. The analysis via Natural Language Processing tools is conducted in two languages and four different countries, such that cultural differences in the tonality and customer needs can be identified for the product. Different methods of sentiment analysis and topic modeling are compared to identify the usability in social media and in the respective languages English and German. Furthermore, we illustrate the importance of preprocessing steps when applying these methods and identify relevant product insights.

Supporting an Expert-centric Process of New Product Introduction With Statistical Machine Learning

Industries that sell products with short-term or seasonal life cycles must regularly introduce new products. Forecasting the demand for New Product Introduction (NPI) can be challenging due to the fluctuations of many factors such as trend, seasonality, or other external and unpredictable phenomena (e.g., COVID-19 pandemic). Traditionally, NPI is an expertcentric process. This paper presents a study on automating the forecast of NPI demands using statistical Machine Learning (namely, Gradient Boosting and XGBoost). We show how to overcome shortcomings of the traditional data preparation that underpins the manual process. Moreover, we illustrate the role of cross-validation techniques for the hyper-parameter tuning and the validation of the models. Finally, we provide empirical evidence that statistical Machine Learning can forecast NPI demand better than experts.