20 research outputs found

    Cloud oriented Additive Technology use for Fast Prototype Development

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    Digitalization has already affected every segment of the industry and especially manufacturing. Based on market requires that are more specific and faster than ever, there is a need to use some of the online platform packages called Cloud Manufacturing (CM). CM operate through the digital data then here comes the expression CAD models or in particular STL files that are currently adequate for Additive Technologies (AT). On the other hand, there is a rapid increase in the measurement aspects via non-contact forms (3D scanners) where their data are stored in various digital formats: IGES, OBJ, PLY, etc.). Those formats can be processed step by step and follow the full path to Reverse Engineering (RE). In this paper will be discussed the possibility of implementing Cloud Additive Technology (CAT) for Fast Prototype Development (FPD) by analyzing the current situation, barriers during incorporation RE and AT, security and technical-economical aspects

    Defect formation in automated fiber placement technology

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    In the frame of this work, a robotic Automated fiber placement - AFP in situ process was applied to obtain high quality thermoplastic composite structures. Automated fiber placement (AFP) with laser assisted heating (LAFP) is an attractive manufacturing technology for the development of lightweight and high performance components, primarily for the aerospace, automotive, military and many other dominant industries worldwide. For the samples laminate plates produced with the AFP procedure, the flexural strength was investigated, and optical images were analyzed for irregularities such as pore content and weaker interlaminar bonding between the layers. Keywords: automated fiber placement, thermoplastic, laser, flexural strength, irregularitie

    Π˜ΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅ Π½Π° моТноститС ΠΈ точноста Π½Π° ΠΎΡ‚ΡΠ»ΠΈΠΊΡƒΠ²Π°ΡšΠ΅ Π½Π° гСомСтриската структура Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½Π°Ρ‚Π° ΠΎΠ΄ ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΡΠΊΠΈΠΎΡ‚ слој со ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈ ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΎΠΌΠ΅Ρ‚Ρ€ΠΈ

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    Π’ΠΎ Ρ€Π°ΠΌΠΊΠΈΡ‚Π΅ Π½Π° ΠΈΠ·Π²Π΅Π΄Π΅Π½ΠΈΡ‚Π΅ ΠΏΡ€ΠΎΠ΄Π»Π°Π±ΠΎΡ‡Π΅Π½ΠΈ Π°Π½Π°Π»ΠΈΡ‚Π»Ρ‡ΠΊΠΈ ΠΈ СкспСримСнтални ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ° ΠΊΠΎΠΈ сС ΠΏΡ€Π΅Π·Π΅Π½Ρ‚ΠΈΡ€Π°Π½ΠΈ Π²ΠΎ Π½Π°ΡƒΡ‡Π½ΠΎ-истраТувачкнот ΠΏΡ€ΠΎΠ΅ΠΊΡ‚ со наслов: Π˜ΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅ Π½Π° моТноститС ΠΈ точноста Π½Π° ΠΎΡ‚ΡΠ»ΠΈΠΊΡƒΠ²Π°ΡšΠ΅ Π½Π° гСомСтрнската структура Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½Π°Ρ‚Π° ΠΎΠ΄ ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΡΠΊΠΈΠΎΡ‚ слој со ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈ ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΎΠΌΠ΅Ρ‚Ρ€ΠΈ создадСна Π΅ Π±Π°Π·Π° со Π½Π½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΠΎΠ΄ Π½Π°ΡƒΡ‡Π΅Π½ ΠΈ Π°ΠΏΠ»ΠΈΠΊΠ°Ρ‚ΠΈΠ²Π΅Π½ ΠΊΠ°Ρ€Π°ΠΊΡ‚Π΅Ρ€, систСматизирана, a сС однСсува Π½Π°: ΠœΠ΅ΡΡ‚ΠΎΡ‚ΠΎ ΠΈ Π·Π½Π°Ρ‡Π΅ΡšΠ΅Ρ‚ΠΎ Π½Π° ΠΌΠ΅Ρ‚Ρ€ΠΎΠ»ΠΎΠ³ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΠΈΡ‚Π΅ Π²ΠΎ инТСнСрската ΠΌΠ΅Ρ‚Ρ€ΠΎΠ»ΠΎΠ³ΠΈΡ˜Π°; ΠœΠ΅Ρ‚ΠΎΠ΄ΠΈΡ‚Π΅ ΠΈ Ρ‚Π΅Ρ…Π½ΠΈΠΊΠΈΡ‚Π΅ Π·Π° ΠΌΠ΅Ρ€Π΅ΡšΠ΅ Π½Π° ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΎΡ‚ Π½Π° рапавоста; ΠšΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈ ΠΈ Π‘Π΅Π·ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈ ΠΌΠ΅Ρ€Π½ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈ: Π‘ΠΏΠΎΡ€Π΅Π΄Π±Π° Π½Π° Ρ€Π°Π·Π½ΠΈΡ‚Π΅ Π²ΠΈΠ΄ΠΎΠ²ΠΈ ΠΌΠ΅Ρ€Π½ΠΈ Ρ‚Π΅Ρ…Π½ΠΈΠΊΠΈ: Π‘Ρ‚Ρ€ΡƒΠΊΡ‚ΡƒΡ€Π° Π½Π° ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈΡ‚Π΅ ΠΌΠ΅Ρ€Π½ΠΈ систСми со Π½Π°Π΄Π²ΠΎΡ€Π΅ΡˆΠ½Π°, ΠΏΡ€ΠΈΠ΄ΠΎΠ΄Π°Π΄Π΅Π½Π° Ρ€Π΅Ρ„Π΅Ρ€Π΅Π½Ρ†Π° ΠΈ со Π²Π½Π°Ρ‚Ρ€Π΅ΡˆΠ½Π°, сопствСна Ρ€Π΅Ρ„Π΅Ρ€Π΅Π½Ρ†Π°; Π’ΠΈΠ΄ΠΎΠ²ΠΈ Π½Π° Ρ‡ΠΈΡ‚Π°Ρ‡ΠΈ ΠΊΠΎΠΈ сС користат кај ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈΡ‚Π΅ ΠΌΠ΅Ρ€Π½Π½ систСми; ΠšΠ°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΡΡ‚ΠΈΠΊΠΈ Π½Π° Π΄ΠΈΠ³ΠΈΡ‚Π°Π»Π½ΠΈΠΎΡ‚ Π΄Π΅Π» ΠΎΠ΄ ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈΡ‚Π΅ ΠΌΠ΅Ρ€Π½ΠΈ систСми Π·Π° ΠΌΠ΅Ρ€Π΅ΡšΠ΅ Π½Π° Π½Π΅Ρ€Π°ΠΌΠ½ΠΈΠ½ΠΈΡ‚Π΅ Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΠΈΡ‚Π΅; Π’ΠΈΠΏΠΎΠ²ΠΈ. Π½Π°ΠΌΠ΅Π½Π° ΠΈ ΠΌΠ΅Ρ‚Ρ€ΠΎΠ»ΠΎΡˆΠΊΠΈ карактСристики Π½Π° Π΅Ρ‚Π°Π»ΠΎΠ½ΠΈΡ‚Π΅ Π·Π° ΠΊΠ°Π»ΠΈΠ±Ρ€Π°Ρ†ΠΈΡ˜Π° Π½Π° систСмитС Π·Π° ΠΌΠ΅Ρ€ΡΡšΡ Π½Π° Ρ‚ΠΎΠΏΠΎΠ³Ρ€Π°Ρ„ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΠΈΡ‚Π΅ (Π’ΠΈΠΏ Al, А2, B1, Π’2, Π’Π—. CI, Π‘2, Π‘Π—, Π‘4, D1, D2, B1, Π•2); ΠŸΡ€Π΅ΠΏΠΎΡ€Π°ΠΊΠΈ ΠΏΡ€ΠΈ ΠΊΠΎΡ€ΠΈΡΡ‚Π΅ΡšΠ΅Ρ‚ΠΎ ΠΈ ΠΊΠ°Π»ΠΈΠ±Ρ€Π°Ρ†ΠΈΡ˜Π°Ρ‚Π° Π½Π° систСмитС Π·Π° ΠΌΠ΅Ρ€Π΅ΡšΠ΅ Π½Π° Ρ‚ΠΎΠΏΠΎΠ³Ρ€Π°Ρ„ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΠΈΡ‚Π΅; Анализа Π½Π° моТноститС Π½Π° ΠΊΠΎΠΌΠΏΡ˜ΡƒΡ‚Π΅Ρ€ΡΠΊΠΈΡ‚Π΅ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΈ Π·Π° ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡƒΠ²Π°ΡšΠ΅, ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ΅ ΠΈ прСсмСтка Π½Π° ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΈΡ‚Π΅ Π½Π° ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΎΡ‚ Π½Π° рапавост: Π”Π΅Ρ„ΠΈΠ½ΠΈΡ€Π°ΡšΠ΅, прСсмСтка Π½ Π·Π½Π°Ρ‡Π΅ΡšΠ΅ Π½Π° ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΈΡ‚Π΅ Π½Π° ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΎΡ‚ Π½Π° рапавост; ΠžΡΡ€Π΅Π΄Π½Π΅Ρ‚ΠΈ, Височински, Π₯ΠΎΡ€ΠΈΠ·ΠΎΠ½Ρ‚Π°Π»Π½ΠΈ ΠΈ Π₯ΠΈΠ±Ρ€ΠΈΠ΄Π½Π½ ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΈ; ΠšΡ€ΠΈΠ²ΠΈ Π½Π° носСњс ΠΈ Rk ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΈ Π½Π° ΠΊΡ€ΠΈΠ²ΠΈΡ‚Π΅; ΠœΠΎΠΆΠ½ΠΎΡΡ‚ΠΈ Π½Π° софтвСрот Talyprofile Π·Π° ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡƒΠ²Π°ΡšΠ΅, Π³Ρ€Π°Ρ„ΠΈΡ‡ΠΊΠ° ΠΈΠ½Ρ‚Π΅Ρ€ΠΏΡ€Π΅Ρ‚Π°Ρ†ΠΈΡ˜Π° ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° Π½Π° ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΎΡ‚ Π½Π° рапавост; ΠŸΡ€ΠΎΡ„ΠΈΠ» Ρ„ΠΈΠ»Ρ‚Ρ€ΠΈ (Гаусов. 2RC-ISО ΠΈ 2RC-PC ΠΏΡ€ΠΎΡ„ΠΈΠ» Ρ„ΠΈΠ»Ρ‚Π΅Ρ€); ΠŸΡ€ΠΈΠΌΠ΅Π½Π° Π½Π° ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΎΡ‚ Microsoft office Excel Π·Π° ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡƒΠ²Π°ΡšΠ΅ Π½Π° Ρ„ΠΈΠ»Ρ‚Π΅Ρ€-срСдна линија Π½Π° ΠΏΡ€ΠΈΠΌΠ°Ρ€Π½ΠΈΠΎΡ‚ ΠΏΡ€ΠΎΡ„ΠΈΠ»ΠΎΡ‚ со ΠΊΠΎΡ€ΠΈΡΡ‚Π΅ΡšΡ Π½Π° Гаусовиот ΠΏΡ€ΠΎΡ„ΠΈΠ» Ρ„ΠΈΠ»Ρ‚Π΅Ρ€; Анализа Π½Π° Π²Π»ΠΈΡ˜Π°Π½ΠΈΠ΅Ρ‚ΠΎ ΠΈΠ° Ρ€Π°Π·Π»ΠΈΡ‡Π½ΠΈΡ‚Π΅ ΠΌΠ΅Ρ€Π½ΠΈ услови Π²ΠΎ процСсот Π½Π° ΠΌΠ΅Ρ€Π΅ΡšΠ΅Ρ‚ΠΎ Π½Π° Ρ‚ΠΎΠΏΠΎΠ³Ρ€Π°Ρ„ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΠΈΡ‚Π΅; ΠŸΠΎΡΡ‚Π°Π²ΡƒΠ²Π°ΡšΠ΅ Π½Π° ΠΌΠ΅Ρ€Π½ΠΈΠΎΡ‚ ΠΏΡ€ΠΈΠΌΠ΅Ρ€ΠΎΠΊ; ΠŸΠΎΡΡ‚Π°Π²ΡƒΠ²Π°ΡšΠ΅ Π½Π° ΠΌΠ΅Ρ€Π΅Π½ ΠΊΠΎΠΎΡ€Π΄ΠΈΠ½Π°Ρ‚ΠΎΠ½ систСм ΠΈ ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡƒΠ²Π°ΡšΠ΅ ΠΏΡ€Π°Π²Ρ†ΠΈ Π·Π° ΠΈΠ·Π²Π΅Π΄ΡƒΠ²Π°ΡšΠ΅ Π½Π° ΠΌΠ΅Ρ€Π΅ΡšΠ°Ρ‚Π°; Π”Π΅Ρ„ΠΈΠ½ΠΈΡ€Π°ΡšΠ΅ Π½Π° основнитС ΠΌΠ΅Ρ€Π½ΠΈ услови ΠΏΡ€ΠΈ 2Π” ΠΌΠ΅Ρ€Π΅ΡšΠ°Ρ‚Π°; ΠŸΠΎΠ·ΠΈΡ†ΠΈΠΎΠ½ΠΈΡ€Π°ΡšΠ΅ Π½Π° Ρ‡ΠΈΡ‚Π°Ρ‡ΠΎΡ‚ Π²Ρ€Π· ΠΌΠ΅Ρ€Π½Π°Ρ‚Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½Π°; Π’Π»ΠΈΡ˜Π°Π½ΠΈΠ΅ Π½Π° Π»ΠΈΠ·Π³Π°Ρ‡ΠΎΡ‚ ΠΈ Π½Π° Π³Π΅ΠΎΠΌΠ΅Ρ‚Ρ€ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΠΌΠ΅Ρ€Π½Π°Ρ‚Π° ΠΈΠ³Π»Π° ΠΏΡ€ΠΈ ΠΊΠΎΠΏΠΈΡ€Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° Ρ‚ΠΎΠΏΠΎΠ³Ρ€Π°Ρ„ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½ΠΈΡ‚Π΅; ΠšΠΎΠ½Ρ‚Ρ€ΠΎΠ»Π° Π½Π° ΡΠΎΡΡ‚ΠΎΡ˜Π±Π°Ρ‚Π° Π½Π° радиусот Π½Π° ΠΌΠ΅Ρ€Π½Π°Ρ‚Π°Π° ΠΈΠ³Π»Π°. Π”Π΅Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΡ˜Π° Π½Π° ΠΌΠ΅Ρ€Π΅Π½Π°Ρ‚Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½Π° (Π‘Ρ‚Π°Ρ‚ΠΈΡ‡ΠΊΠΈ ΠΈ Π”ΠΈΠ½Π°ΠΌΠΈΡ‡ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»); Π’Π»ΠΈΡ˜Π°Π½ΠΈΠ΅ Π½Π° сСмплирачката Π±Ρ€Π·ΠΈΠ½Π°, сСмплирачкото Ρ€Π°ΡΡ‚ΠΎΡ˜Π°Π½ΠΈΠ΅ ΠΈ Π½Π° Π²ΠΊΡƒΠΏΠ½Π°Ρ‚Π° ΠΌΠ΅Ρ€Π½Π° Π΄ΠΎΠ»ΠΆΠΈΠ½Π°; Π’Π»ΠΈΡ˜Π°Π½ΠΈΠ΅ Π½Π° Π³ΠΎΠ»Π΅ΠΌΠΈΠ½Π°Ρ‚Π° Π½Π° радиусот Π½Π° Π·Π°ΠΎΠ±Π»ΡƒΠ²Π°ΡšΠ΅ Π½Π° Π²Ρ€Π²ΠΎΡ‚ ΠΎΠ΄ ΠΌΠ΅Ρ€Π½Π°Ρ‚Π° ΠΈΠ³Π»Π° ΠΈ Π½Π° соодносот ΠΏΠΎΠΌΠ΅Ρ“Ρƒ ΠΌΠ΅Ρ€Π½Π°Ρ‚Π° сила ΠΈ Π±Ρ€Π·ΠΈΠ½Π°Ρ‚Π° Π½Π° ΠΌΠ΅Ρ€Π΅ΡšΠ΅; Π’Π»ΠΈΡ˜Π°Π½ΠΈΠ΅ Π½Π° карактСристикитС ΠΈΠ° ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Ρ‚ΠΈΠΎΡ‚ трансформатор ΠΈ ΠΏΠ° Ρ„Ρ€Π΅ΠΊΠ²Π΅Π½Ρ†ΠΈΡ˜Π°Ρ‚Π° Π½Π° сниусоиднниот сигнал Π²Ρ€Π· карактСристикитС Π½Π° Π΄ΠΈΡ„Π΅Ρ€Π΅Π½Ρ†ΠΈΡ˜Π°Π»Π½ΠΈΠΎΡ‚ трансформатор ΠΈ Π’Π»ΠΈΡ˜Π°Π½ΠΈΠ΅ Π½Π° ΠΊΠ²Π°Π½Ρ‚ΠΈΠ·Π°Ρ†ΠΈΡ˜Π°Ρ‚Π° Π½Π° Π°Π½Π°Π»ΠΎΠ³Π½ΠΈΠΎΡ‚ сигнал; Бтатистички ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΈ Π½Π° рапавост Π²ΠΎ Π—Π” Π΄ΠΎΠΌΠ΅Π½. Π—Π° Π΄ΠΈΡ˜Π°Π³Π½ΠΎΡΡ‚ΠΈΡ†ΠΈΡ€Π°ΡšΠ΅ Π½Π° условитС ΠΏΡ€ΠΈ ΠΊΠΎΠΈ сС создава ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚Π΅Π½Π°Ρ‚Π° ΠΏΠΎΠ²Ρ€ΡˆΠΈΠ½Π° создадСн Π΅ ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³ систСм Π·Π° слСдСњС Π½Π° условитС ΠΏΡ€ΠΈ ΠΊΠΎΠΈ сС ΠΈΠ·Π²Π΅Π΄ΡƒΠ²Π°Π°Ρ‚ СкспСримСнталнитС ΠΈΡΡ‚Ρ€Π°ΠΆΡƒΠ²Π°ΡšΠ° Π½Π° процСсот Π½Π° ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠ° со ΡΡ‚Ρ€ΡƒΠΆΠ΅ΡšΠ΅. ΠžΡ‚ΠΏΠΎΡ€ΠΈΡ‚Π΅ ΠΈ Ρ‚Π΅ΠΌΠΏΠ΅Ρ€Π°Ρ‚ΡƒΡ€Π°Ρ‚Π° Π²ΠΎ процСсот Π½Π° Ρ€Π΅ΠΆΠ΅ΡšΠ΅ сС ΠΎΠ΄Π±Ρ€Π°Π½ΠΈ ΠΊΠ°ΠΊΠΎ ΠΈΠ½Π΄ΠΈΠΊΠ°Ρ‚ΠΎΡ€ΠΈ Π·Π° слСдСњС Π½Π° ΠΏΠΎΡ˜Π°Π²Π°Ρ‚Π° Π½Π° Π²ΠΈΠ±Ρ€Π°Ρ†ΠΈΠΈ ΠΈ Π²Π»ΠΈΡ˜Π°Π½ΠΈΡ˜Π°Ρ‚Π° Π·Π° појава Π½Π° гСомСтрискитС ΠΎΡ‚ΡΡ‚Π°ΠΏΡƒΠ²Π°ΡšΠ°. ПосСбно мСсто Π΅ посвСтСно Π½Π° ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ°Ρ‚Π° Π·Π° ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡƒΠ²Π°ΡšΠ΅ Π½Π° ΠΌΠ΅Ρ€Π½Π°Ρ‚Π° нСодрССдност Π½Π° Ρ€Π΅Π·ΡƒΠ»Ρ‚Π°Ρ‚ΠΈΡ‚Π΅ ΠΎΠ΄ ΠΌΠ΅Ρ€Π΅ΡšΠ΅Ρ‚ΠΎ Π½Π° рапавоста со ΠΏΡ€ΠΈΠΌΠ΅Π½Π° ΠΈΠ° ΠΊΠΎΠ½Ρ‚Π°ΠΊΡ‚Π½ΠΈ ΠΌΠ΅Ρ€Π½ΠΈ ΡƒΡ€Π΅Π΄ΠΈ. Π’ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°Ρ‚Π° Π΅ Π²ΠΊΠ»ΡƒΡ‡Π΅Π½Π° продлабочсна ΡΠΈΡΡ‚Π΅ΠΌΠ°Ρ‚ΠΈΠ·Π°Ρ†ΠΈΡ˜Π° Π½Π° ΠΌΠΎΠΆΠ½ΠΈΡ‚Π΅ ΠΈΠ·Π²ΠΎΡ€ΠΈ Π½Π° Π³Ρ€Π΅ΡˆΠΊΠΈΡ‚Π΅ ΠΏΡ€ΠΈ ΠΌΠ΅Ρ€Π΅ΡšΠ΅ Π½Π° рапавоста, ΠΊΠΎΠΈ Π±ΠΈ Ρ‚Ρ€Π΅Π±Π°Π»ΠΎ Π΄Π° сС Π·Π΅ΠΌΠ°Π°Ρ‚ Π²ΠΎ ΠΏΡ€Π΅Π΄Π²ΠΈΠ΄ ΠΏΡ€ΠΈ ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡƒΠ²Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° нСодрСдСноста Π½Π° Ρ€Π΅Π·ΡƒΠ»Ρ‚Π°Ρ‚ΠΈΡ‚Π΅, прСтставСни со Π΄ΠΈΡ˜Π°Π³Ρ€Π°ΠΌΠΎΡ‚ ΠΏΠ° Ишикава

    Avoiding heavy computations in inverse calibration procedure for 7 DOF robot manipulator

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    Procedure for determining commanded coordinates in machine space if desired coordinates are given is inverse calibration. A large amount of data is considered after measurement procedure and it is essential to locate desired point in the real space which is skewed due to measured geometric errors. The machine workspace is divided to cells using measurement points. It is depicted the importance of finding the proper cell in skewed 3D lat- tice, for calibration of translational axes of ATL machine with large workspace. To calibrate 7 DOF robot manipula- tor, this algorithm is extended. The problem of finding the proper cell in 7D skewed grid needs heavy computations and takes significant amount of computational time. Few ideas for avoiding these computations are described and the influence on the final precision of the calibration procedure is explored

    Volumetric calibration for improving accuracy of AFP/ATL machines

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    Automated Fiber Placement (AFP) and Automated Tape Laying (ATL) technologies are mostly used in aerospace industry. Deviations from predefined position and orientation of the AFP/ATL machine’s end-effector may cause defects of the final product like gaps and laps of the laminate ply, tow end placement errors, pressure and temperature variations, etc. That makes clear the importance of accuracy of AFP/ATL machines. Calibration is needed to enhance accuracy. Development and implementation of a comprehensive procedure for volumetric calibration of three linear axes is described in this paper. According to ISO 230-1:2012 and ISO 230-2:2014 standards, 18 position dependent and 3 position independent (in total 21) errors of the 3 linear axes are considered. Measurements are performed using laser interferometer on ATL machine produced by company Mikrosam. Obtained data are used for calibration of that machine and validity of the results is verified by comparison with the calibration results obtained by TRAC-CAL software developed by ETALON AG

    Some Experimental Investigation of Products from Thermoplastic Composite Materials Manufactured with Robot and LAFP

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    For successful avoiding of the irregularities and errors in the products from composite materials, it is important to manage the whole production process in real time. This applies to detecting certain irregularities (positioning defects, bonding defects), controlling the robot and process parameters. This paper presents results from an experimental study of the influence of embedded defects created during in - situ laser automated fiber tape placement (LAFP), on the mechanical properties of carbon/PEEK composites. Three rings have been examined with different designs [(0/±45˚)n], [(0/±30˚)n] and [(0/±90˚)n], in which gaps and overlaps have been introduced during fiber placement. The microstructures were characterized by optic microscopy. ILSS tests were performed on samples from rings and showed that the presence of a gap/overlap and voids more than 3% affect mechanical behavior of pipes but does not affect degree of crystallinity

    Application of decision making method (AHP) in Reverse Engineering and Additive Manufacturing Technologies

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    Continuous market demand shows a fast transition of Additive Manufacturing (AM) from prototype to regular production. The different complex parts are easier to manage using 3D scanners and applying Reverse Engineering (RE) to convert them into digital data that can be reproduced again. Through this paper we intend to explain the relationship between RE and AM with decision making methodology by applying AHP hierarchy, including: goals, criteria, sub-criteria and alternatives. Case study presented confirm the efficiency of the proposed methodology for decision making in production technology

    Algorithmic approach to geometric solution of generalized Paden–Kahan subproblem and its extension

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    Kinematics as a science of geometry of motion describes motion by means of position, orientation, and their time derivatives. The focus of this article aims screw theory approach for the solution of inverse kinematics problem. The kinematic elements are mathematically assembled through screw theory by using only the base, tool, and workpiece coordinate systemsβ€”opposite to conventional Denavit–Hartenberg approach, where at least n ΓΎ 1 coordinate frames are needed for a robot manipulator with n joints. The inverse kinematics solution in Denavit–Hartenberg convention is implicit. Instead, explicit solutions to inverse kinematics using the Paden–Kahan subproblems could be expressed. This article gives step-by-step application of geometric algorithm for the solution of all the cases of Paden–Kahan subproblem 2 and some extension of that subproblem based on subproblem 2. The algorithm described here covers all of the cases that can appear in the generalized subproblem 2 definition, which makes it applicable for multiple movement configurations. The extended subproblem is used to solve inverse kinematics of a manipulator that cannot be solved using only three basic Paden–Kahan subproblems, as they are originally formulated. Instead, here is provided solution for the case of three subsequent rotations, where last two axes are parallel and the first one does not lie in the same plane with neither of the other axes. Since the inverse kinematics problem may have no solution, unique solution, or many solutions, this article gives a thorough discussion about the necessary conditions for the existence and number of solutions. Keywords Screw motion, Paden–Kahan subproblem, geometric algorithm, inverse kinematics, mathematical foundation

    Influence of the Process Parameters on Laser - Assisted Automated Tape Placement Process

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    Thermoplastic part manufacture by laser-assisted automated tape placement (LATP) process has a high potential for the cost-effective production. Within the frames of this paper it was applied a designing of the industrial LATP process, i.e. planning of the experiments and on the basis of the plan matrix, the specimens were manufactured. Namely, two different thermoplastic prepreg materials were used based on polyphenylene sulfide (PPS) and polyether ether ketone (PEEK) and carbon fibers. The planning of experiments was made separately for processing of these prepreg materials and as the most influenced factors were taken: laser temperature, compact pressure of roller and laser placement angle. For all manufactured specimens the flexural strength was tested and on the basis of the received experimental data it was created the regression equitations which the best describes the processes. This research present and discuss some of laser control system variables and final properties of composite panel specimens

    Influence Of Each Of The Geometric Errors On The Total Displacement Error Of The Machine

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    An algorithm for volumetric calibration is developed and verified practically by measuring of all geometric errors after numerical compensation. In this paper, analysis of the contribution of each of 9 translational and 9 rotational position dependent errors and each of 3 position independent errors in total displacement error vector is presented. Changing only one of the errors, and keeping all the others unchanged, the final total error is examined using the simulation based on forward calibration part of the calibration algorithm. The measurement of all 21 volumetric errors is expensive and time consuming. Instead of numerical compensation in the controller, this analysis yields opportunity to enhance accuracy of the machine, measuring and making correction of only few of the geometric errors. Results from the simulation showed that position independent errors have most significant influence on total displacement error. Decreasing of the squareness error S XY improves the mean of norms of total displacement vectors about 25%, and percentage of improvement for squareness error S ZX is about 20%. If all squareness errors are reduced by factor 0.04, then total improvement is more than 51%
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