UPAYA MENINGKATKAN MOTIVASI BELAJAR DAN PEMAHAMAN SISWA PADA MATA PELAJARAN GAMBAR TEKNIK MELALUI MODEL PEMBELAJARAN PROBLEM-BASED LEARNING (PBL) (Penelitian Tindakan Kelas Pada Siswa Kelas X SMK Negeri 5 Surakarta Tahun Ajaran 2016/2017)

ABSTRACT Maris Syaputra. K2513086. Efforts increase the motivation of learning and understanding of Students on subjects Engineering Drawings the Learning Model of Problem-Based Learning (PBL) (Research Action classes for Students of class X SMK Negeri 5 Surakarta Academic Year 2016/2017). Essay. Teaching and Education Faculty Sebelas Maret University. June 2017. The purpose of this research was to improve the motivation of learning and understanding of students on subjects Engineering Drawings the learning model of Problem-Based Learning (PBL) in Student of Class X SMK Negeri 5 Surakarta in the academic year 2016/2017. This research was a class room action research. It consisted of two cycles. Each cycle consisted of four stages, namely the planning stages, Implementation stage, stage of observation and reflection phase. The subject of this research was the student of the class X at SMK Negeri 5 Surakarta amounted to 32 students. Data source derived from teachers, students and documents. Data collection techniques used were an observation, an interview, a tests and a documentation. The results showed the achievement of motivation of learning and the understanding of engineering drawings as that is evidenced by the increase in the value of learning motivation and understanding on subjects Engineering Drawings. Prior to the act as much as 10 students who get the value of motivation in both categories, Cycle I up to 18 students, and in cycle II rose to 28 students, and the average value understanding Engineering Drawings students on before action of 60.5 while rising to 75.96 Cycle I and cycle II rose to 81.09. Based on the results of the study show that the learning Problem-Based Learning (PBL) can increase the motivation of learning and understanding of students on subjects of Engineering Drawings at the class X of SMK Negeri 5 Surakarta in the academic year 2016/2017. Keywords: Learning Motivation, Student Understanding, Engineering Drawings, Problem-based learnin

Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks.

Engineering drawings are common across different domains such as Oil & Gas, construction, mechanical and other domains. Automatic processing and analysis of these drawings is a challenging task. This is partly due to the complexity of these documents and also due to the lack of dataset availability in the public domain that can help push the research in this area. In this paper, we present a multiclass imbalanced dataset for the research community made of 2432 instances of engineering symbols. These symbols were extracted from a collection of complex engineering drawings known as Piping and Instrumentation Diagram (P&ID). By providing such dataset to the research community, we anticipate that this will help attract more attention to an important, yet overlooked industrial problem, and will also advance the research in such important and timely topics. We discuss the datasets characteristics in details, and we also show how Convolutional Neural Networks (CNNs) perform on such extremely imbalanced datasets. Finally, conclusions and future directions are discussed

Explicit and persistent knowledge in engineering drawing analysis

technical reportDomain knowledge permeates all aspects of the engineering drawing analysis process, including understanding the physical processes operating on the medium (i.e., paper), the image analysis techniques, and the interpretation semantics of the structural layout and contents of the drawing. Additionally, an understanding of the broader reverse engineering context, within which the drawing analysis takes place, should be exploited. Thus as part of a wider project on the reverse engineering of legacy systems, we have developed an agent-based engineering analysis system called NDAS (nonDeterministic Agent System). In this paper, we discuss the nature of such a system and how knowledge can be made explicit (both for agents and humans) and how performance models can be de?ned, calibrated, monitored, and improved over time through the use of persistent knowledge. A framework is proposed that allows computational agents to: (1) explore the threshold space for an optimal analysis of the drawing, (2) control information gain through agent invocation, (3) incorporate and communicate knowledge, and (4) inform the software engineering and system development with deep knowledge of the relationships between modules and their parameters (at least in a statistical sense)

A Review of Neural Network Approach on Engineering Drawing Recognition and Future Directions

Engineering Drawing (ED) digitization is a crucial aspect of modern industrial processes, enabling efficient data management and facilitating automation. However, the accurate detection and recognition of ED elements pose significant challenges. This paper presents a comprehensive review of existing research on ED element detection and recognition, focusing on the role of neural networks in improving the analysis process. The study evaluates the performance of the YOLOv7 model in detecting ED elements through rigorous experimentation. The results indicate promising precision and recall rates of up to 87.6% and 74.4%, respectively, with a mean average precision (mAP) of 61.1% at IoU threshold 0.5. Despite these advancements, achieving 100% accuracy remains elusive due to factors such as symbol and text overlapping, limited dataset sizes, and variations in ED formats. Overcoming these challenges is vital to ensuring the reliability and practical applicability of ED digitization solutions. By comparing the YOLOv7 results with previous research, the study underscores the efficacy of neural network-based approaches in handling ED element detection tasks. However, further investigation is necessary to address the challenges above effectively. Future research directions include exploring ensemble methods to improve detection accuracy, fine-tuning model parameters to enhance performance, and incorporating domain adaptation techniques to adapt models to specific ED formats and domains. To enhance the real-world viability of ED digitization solutions, this work highlights the importance of conducting testing on diverse datasets representing different industries and applications. Additionally, fostering collaborations between academia and industry will enable the development of tailored solutions that meet specific industrial needs. Overall, this research contributes to understanding the challenges in ED digitization and paves the way for future advancements in this critical field

АНАЛІЗ ОСНОВНИХ МЕТОДІВ РОЗПІЗНАВАННЯ КРЕСЛЕНЬ ТА МОЖЛИВОСТЕЙ ТРАНСФОРМАЦІЇ З 2D У 3D

The article presents an analysis of the main methods for recognizing drawings and the possibilities of transforming two-dimensional models (2D) into three-dimensional models (3D). Despite the rapid development of IT, the question of accuracy and speed of transformation of two-dimensional models into three-dimensional ones remains open. As machine design technologies and corresponding automated decision-making systems (CAD) develop, the number of methods and models that can potentially be used in the task of drawing recognition and 2D to 3D transformation is rapidly increasing. Today, there are quite a large number of methods for recognizing drawings and converting them into a three-dimensional model, but each of them has a certain number of shortcomings. Therefore, there is a need to carry out a comprehensive analysis of these methods, which can potentially be applied in the context of solving problems of drawing recognition and 2D to 3D transformation. It should be noted that there is a contradiction between the traditional procedure for preparing drawing documentation on paper media until the 80s and 90s of the 20th century and the new methods of 3D modelling that have been developed since the mid-90s. This gives designers truly unlimited opportunities to prepare design and technical documentation, without focusing on the problem of preparing design and drawing documentation and the features of entering input data. Application software significantly facilitates this process. Note that most 3D systems (for example, software products Autodesk TinkerCAD, DesignSpark Mechanical, FreeCAD, Autodesk AutoCAD, ZBrush, Blender, etc.) use approaches that allow synthesizing a frame or boundary representation of an object modelled in space. Professional systems (for example Autodesk 3ds Max, Autodesk Maya) use generalized models of spatial objects. This idea assumes that the designers have appropriate information arrays, which a priori should correspond to all projections of the object in the three main planes.У статті викладено аналіз основних методів для розпізнавання креслень та можливостей трансформації двовимірних моделей (2D) у тривимірні моделі (3D). Незважаючи на швидкий розвиток ІТ все ж питання точності та швидкості перетворення двовимірних моделей у тривимірні залишається відкритим. В міру розвитку технологій машинного проектування та відповідних систем автоматизованого прийняття рішень (САПР) кількість методів і моделей, які можуть бути потенційно використані в задачі розпізнавання креслень та трансформації  стрімко зростає. На сьогоднішній день існує достатньо велика кількість методів розпізнавання креслень та їх перетворення у тривимірну модель, проте кожен із них має певну кількість недоліків. Тому є потреба проведення комплексного аналізу даних методів, які потенційно можуть бути застосовані у контексті вирішення завдань розпізнавання креслень та трансформації . Слід зазначити, що існує суперечність між традиційною процедурою підготовки креслярської документації на паперових носіях до 80-90-х років 20-го століття та новими методами 3D моделювання, що отримали розвиток із середини 90-х років. Це дає дійсно безмежні можливості конструкторам готувати проектно-технічну документацію, не зациклюючись на проблемі підготовки креслярсько-конструкторської документації та особливостях введення вихідних даних. Істотно полегшує цей процес застосування прикладного програмного забезпечення. Зауважимо, що в більшості систем 3D (наприклад, програмні продукти Autodesk TinkerCAD, DesignSpark Mechanical, FreeCAD, Autodesk AutoCAD, ZBrush, Blender та ін.) застосовуються підходи, які дозволяють синтезувати каркасне або граничне уявлення об’єкта, що моделюється в просторі. У професійних системах (наприклад Autodesk 3ds Max, Autodesk Maya) використовують узагальнені моделі просторових об’єктів. Таке уявлення передбачає наявність у проектувальників відповідних інформаційних масивів, які апріорі повинні відповідати всім проекціям об’єкта у трьох основних площинах

Piirustusten kulutuksen paradigman muuttaminen

Drawings have existed from the early times of mankind as a means of communicating thoughts forward, crystallizing ideas or simply for the sake of remembering something. While the production and delivery methods of drawings in the construction industry may have improved over the years, especially during the past few decades, the way to consume drawings has not progressed correspondingly. This research seeks to provide a comprehensive overview on the possibilities that may emerge from improvements in the process of drawing consumption, as well as to function as a guideline for anyone trying to understand the consumption of drawings as a practice, and furthermore, for anyone who may be interested in developing new technologies that specifically improve the consumption process of drawings. Findings of the study could potentially be used as a reference when developing new technologies, or at minimum they will contribute to the body of knowledge on the process of drawing consumption and on the philosophical qualities of drawings – which are topics that have not been studied extensively. As the title of the thesis suggests, an underlying hypothesis of the study is that a paradigm shift in the field of drawing consumption is something that – if attained – would allow the industry to transcend their current practices by improving the industry holistically. The research consists of two parts: a theoretical study during which the qualities and practices of drawing consumption are studied thoroughly, and a proof-of-concept study, that is an attempt to introduce a new technology in a form of a prototype that could work as a guideline or a contribution for any party interested in further research or development regarding the subject.Piirustukset ovat olleet olemassa niin kauan kuin ihmisetkin, palvellen heidän kommunikointitarpeitaan, selkeyttääkseen ajattelua tai yksinkertaisesti muistin tukena. Vaikka rakennusalalla piirustusten tuotanto- ja toimitusmenetelmät ovat kehittyneetkin vuosien saatossa, etenkin viimeisten muutamien vuosikymmenien aikana, piirustusten kulutusprosessi ei ole kehittynyt vastaavasti. Tämän tutkimuksen pyrkimyksenä on tarjota kokonaisvaltainen kuva mahdollisuuksista joita voi seurata parannuksista piirustusten kulutusprosessissa, sekä toimia opasteena niille tahoille jotka haluavat ymmärtää piirustusten kulutusta prosessina – ja edelleen keille tahansa jotka ovat kiinnostuneita kehittämään uusia teknologioita spesifisti piirustusten kulutusprosessin parantamiseksi. Tutkimuksen löydöksiä voidaan hyödyntää referenssinä uusia teknologioita kehittäessä, tai vähintäänkin ne palvelevat kasvattamalla sekä teoreettista ymmärrystä piirustusten kulutusprosessiin liittyen että piirustusten filosofisiin ominaisuuksiin liittyen. Kyseessä ovat aiheet joista ei löydy kattavaa tutkimustietoa ennestään. Kuten työn otsikko antaa ymmärtää, tutkimuksen perimmäisenä hypoteesina on olettamus siitä että paradigmamuutos piirustusten kulutusprosessiin liittyen auttaisi rakennusalaa pääsemään uudelle tasolle toimintatavoissaan edesauttaen alaa kokonaisvaltaisesti. Tutkimus koostuu kahdesta osa-alueesta: Ensimmäinen osa on teoreettinen tutkimus, jonka aikana piirustusten ominaisuuksia ja prosesseja tutkitaan perusteellisesti. Toinen osa on käytännön tutkimus, jossa esitellään uusi teknologia prototyypin muodossa, joka voi toimia opasteena tai kontribuutiona kenelle tahansa osapuolelle, joka on kiinnostunut aiheeseen liittyvästä tutkimuksesta tai tuotekehityksestä