20 research outputs found
Cloud oriented Additive Technology use for Fast Prototype Development
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
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
ΠΡΡΡΠ°ΠΆΡΠ²Π°ΡΠ΅ Π½Π° ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈΡΠ΅ ΠΈ ΡΠΎΡΠ½ΠΎΡΡΠ° Π½Π° ΠΎΡΡΠ»ΠΈΠΊΡΠ²Π°ΡΠ΅ Π½Π° Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠΊΠ°ΡΠ° ΡΡΡΡΠΊΡΡΡΠ° Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½Π°ΡΠ° ΠΎΠ΄ ΠΏΠΎΠ²ΡΡΠΈΠ½ΡΠΊΠΈΠΎΡ ΡΠ»ΠΎΡ ΡΠΎ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈ ΠΏΡΠΎΡΠΈΠ»ΠΎΠΌΠ΅ΡΡΠΈ
ΠΠΎ ΡΠ°ΠΌΠΊΠΈΡΠ΅ Π½Π° ΠΈΠ·Π²Π΅Π΄Π΅Π½ΠΈΡΠ΅ ΠΏΡΠΎΠ΄Π»Π°Π±ΠΎΡΠ΅Π½ΠΈ Π°Π½Π°Π»ΠΈΡΠ»ΡΠΊΠΈ ΠΈ Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»Π½ΠΈ ΠΈΡΡΡΠ°ΠΆΡΠ²Π°ΡΠ° ΠΊΠΎΠΈ ΡΠ΅ ΠΏΡΠ΅Π·Π΅Π½ΡΠΈΡΠ°Π½ΠΈ Π²ΠΎ Π½Π°ΡΡΠ½ΠΎ-ΠΈΡΡΡΠ°ΠΆΡΠ²Π°ΡΠΊΠ½ΠΎΡ ΠΏΡΠΎΠ΅ΠΊΡ ΡΠΎ Π½Π°ΡΠ»ΠΎΠ²: ΠΡΡΡΠ°ΠΆΡΠ²Π°ΡΠ΅ Π½Π° ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈΡΠ΅ ΠΈ ΡΠΎΡΠ½ΠΎΡΡΠ° Π½Π° ΠΎΡΡΠ»ΠΈΠΊΡΠ²Π°ΡΠ΅ Π½Π° Π³Π΅ΠΎΠΌΠ΅ΡΡΠ½ΡΠΊΠ°ΡΠ° ΡΡΡΡΠΊΡΡΡΠ° Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½Π°ΡΠ° ΠΎΠ΄ ΠΏΠΎΠ²ΡΡΠΈΠ½ΡΠΊΠΈΠΎΡ ΡΠ»ΠΎΡ ΡΠΎ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈ ΠΏΡΠΎΡΠΈΠ»ΠΎΠΌΠ΅ΡΡΠΈ ΡΠΎΠ·Π΄Π°Π΄Π΅Π½Π° Π΅ Π±Π°Π·Π° ΡΠΎ Π½Π½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΎΠ΄ Π½Π°ΡΡΠ΅Π½ ΠΈ Π°ΠΏΠ»ΠΈΠΊΠ°ΡΠΈΠ²Π΅Π½ ΠΊΠ°ΡΠ°ΠΊΡΠ΅Ρ, ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·ΠΈΡΠ°Π½Π°, a ΡΠ΅ ΠΎΠ΄Π½Π΅ΡΡΠ²Π° Π½Π°: ΠΠ΅ΡΡΠΎΡΠΎ ΠΈ Π·Π½Π°ΡΠ΅ΡΠ΅ΡΠΎ Π½Π° ΠΌΠ΅ΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ°ΡΠ° Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½ΠΈΡΠ΅ Π²ΠΎ ΠΈΠ½ΠΆΠ΅Π½Π΅ΡΡΠΊΠ°ΡΠ° ΠΌΠ΅ΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ°; ΠΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ ΠΈ ΡΠ΅Ρ
Π½ΠΈΠΊΠΈΡΠ΅ Π·Π° ΠΌΠ΅ΡΠ΅ΡΠ΅ Π½Π° ΠΏΡΠΎΡΠΈΠ»ΠΎΡ Π½Π° ΡΠ°ΠΏΠ°Π²ΠΎΡΡΠ°; ΠΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈ ΠΈ ΠΠ΅Π·ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈ ΠΌΠ΅ΡΠ½ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ: Π‘ΠΏΠΎΡΠ΅Π΄Π±Π° Π½Π° ΡΠ°Π·Π½ΠΈΡΠ΅ Π²ΠΈΠ΄ΠΎΠ²ΠΈ ΠΌΠ΅ΡΠ½ΠΈ ΡΠ΅Ρ
Π½ΠΈΠΊΠΈ: Π‘ΡΡΡΠΊΡΡΡΠ° Π½Π° ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈΡΠ΅ ΠΌΠ΅ΡΠ½ΠΈ ΡΠΈΡΡΠ΅ΠΌΠΈ ΡΠΎ Π½Π°Π΄Π²ΠΎΡΠ΅ΡΠ½Π°, ΠΏΡΠΈΠ΄ΠΎΠ΄Π°Π΄Π΅Π½Π° ΡΠ΅ΡΠ΅ΡΠ΅Π½ΡΠ° ΠΈ ΡΠΎ Π²Π½Π°ΡΡΠ΅ΡΠ½Π°, ΡΠΎΠΏΡΡΠ²Π΅Π½Π° ΡΠ΅ΡΠ΅ΡΠ΅Π½ΡΠ°; ΠΠΈΠ΄ΠΎΠ²ΠΈ Π½Π° ΡΠΈΡΠ°ΡΠΈ ΠΊΠΎΠΈ ΡΠ΅ ΠΊΠΎΡΠΈΡΡΠ°Ρ ΠΊΠ°Ρ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈΡΠ΅ ΠΌΠ΅ΡΠ½Π½ ΡΠΈΡΡΠ΅ΠΌΠΈ; ΠΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ Π½Π° Π΄ΠΈΠ³ΠΈΡΠ°Π»Π½ΠΈΠΎΡ Π΄Π΅Π» ΠΎΠ΄ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈΡΠ΅ ΠΌΠ΅ΡΠ½ΠΈ ΡΠΈΡΡΠ΅ΠΌΠΈ Π·Π° ΠΌΠ΅ΡΠ΅ΡΠ΅ Π½Π° Π½Π΅ΡΠ°ΠΌΠ½ΠΈΠ½ΠΈΡΠ΅ Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½ΠΈΡΠ΅; Π’ΠΈΠΏΠΎΠ²ΠΈ. Π½Π°ΠΌΠ΅Π½Π° ΠΈ ΠΌΠ΅ΡΡΠΎΠ»ΠΎΡΠΊΠΈ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ Π½Π° Π΅ΡΠ°Π»ΠΎΠ½ΠΈΡΠ΅ Π·Π° ΠΊΠ°Π»ΠΈΠ±ΡΠ°ΡΠΈΡΠ° Π½Π° ΡΠΈΡΡΠ΅ΠΌΠΈΡΠ΅ Π·Π° ΠΌΠ΅ΡΡΡΡ Π½Π° ΡΠΎΠΏΠΎΠ³ΡΠ°ΡΠΈΡΠ°ΡΠ° Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½ΠΈΡΠ΅ (Π’ΠΈΠΏ Al, Π2, B1, Π2, ΠΠ. CI, Π‘2, Π‘Π, Π‘4, D1, D2, B1, Π2); ΠΡΠ΅ΠΏΠΎΡΠ°ΠΊΠΈ ΠΏΡΠΈ ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ΅ΡΠΎ ΠΈ ΠΊΠ°Π»ΠΈΠ±ΡΠ°ΡΠΈΡΠ°ΡΠ° Π½Π° ΡΠΈΡΡΠ΅ΠΌΠΈΡΠ΅ Π·Π° ΠΌΠ΅ΡΠ΅ΡΠ΅ Π½Π° ΡΠΎΠΏΠΎΠ³ΡΠ°ΡΠΈΡΠ°ΡΠ° Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½ΠΈΡΠ΅; ΠΠ½Π°Π»ΠΈΠ·Π° Π½Π° ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈΡΠ΅ Π½Π° ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΡΠΊΠΈΡΠ΅ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΈ Π·Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ²Π°ΡΠ΅, ΠΈΡΡΡΠ°ΠΆΡΠ²Π°ΡΠ΅ ΠΈ ΠΏΡΠ΅ΡΠΌΠ΅ΡΠΊΠ° Π½Π° ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ Π½Π° ΠΏΡΠΎΡΠΈΠ»ΠΎΡ Π½Π° ΡΠ°ΠΏΠ°Π²ΠΎΡΡ: ΠΠ΅ΡΠΈΠ½ΠΈΡΠ°ΡΠ΅, ΠΏΡΠ΅ΡΠΌΠ΅ΡΠΊΠ° Π½ Π·Π½Π°ΡΠ΅ΡΠ΅ Π½Π° ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΡΠ΅ Π½Π° ΠΏΡΠΎΡΠΈΠ»ΠΎΡ Π½Π° ΡΠ°ΠΏΠ°Π²ΠΎΡΡ; ΠΡΡΠ΅Π΄Π½Π΅ΡΠΈ, ΠΠΈΡΠΎΡΠΈΠ½ΡΠΊΠΈ, Π₯ΠΎΡΠΈΠ·ΠΎΠ½ΡΠ°Π»Π½ΠΈ ΠΈ Π₯ΠΈΠ±ΡΠΈΠ΄Π½Π½ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈ; ΠΡΠΈΠ²ΠΈ Π½Π° Π½ΠΎΡΠ΅ΡΡ ΠΈ Rk ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈ Π½Π° ΠΊΡΠΈΠ²ΠΈΡΠ΅; ΠΠΎΠΆΠ½ΠΎΡΡΠΈ Π½Π° ΡΠΎΡΡΠ²Π΅ΡΠΎΡ Talyprofile Π·Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ²Π°ΡΠ΅, Π³ΡΠ°ΡΠΈΡΠΊΠ° ΠΈΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΠΈΡΠ° ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° Π½Π° ΠΏΡΠΎΡΠΈΠ»ΠΎΡ Π½Π° ΡΠ°ΠΏΠ°Π²ΠΎΡΡ; ΠΡΠΎΡΠΈΠ» ΡΠΈΠ»ΡΡΠΈ (ΠΠ°ΡΡΠΎΠ². 2RC-ISΠ ΠΈ 2RC-PC ΠΏΡΠΎΡΠΈΠ» ΡΠΈΠ»ΡΠ΅Ρ); ΠΡΠΈΠΌΠ΅Π½Π° Π½Π° ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΎΡ Microsoft office Excel Π·Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ²Π°ΡΠ΅ Π½Π° ΡΠΈΠ»ΡΠ΅Ρ-ΡΡΠ΅Π΄Π½Π° Π»ΠΈΠ½ΠΈΡΠ° Π½Π° ΠΏΡΠΈΠΌΠ°ΡΠ½ΠΈΠΎΡ ΠΏΡΠΎΡΠΈΠ»ΠΎΡ ΡΠΎ ΠΊΠΎΡΠΈΡΡΠ΅ΡΡ Π½Π° ΠΠ°ΡΡΠΎΠ²ΠΈΠΎΡ ΠΏΡΠΎΡΠΈΠ» ΡΠΈΠ»ΡΠ΅Ρ; ΠΠ½Π°Π»ΠΈΠ·Π° Π½Π° Π²Π»ΠΈΡΠ°Π½ΠΈΠ΅ΡΠΎ ΠΈΠ° ΡΠ°Π·Π»ΠΈΡΠ½ΠΈΡΠ΅ ΠΌΠ΅ΡΠ½ΠΈ ΡΡΠ»ΠΎΠ²ΠΈ Π²ΠΎ ΠΏΡΠΎΡΠ΅ΡΠΎΡ Π½Π° ΠΌΠ΅ΡΠ΅ΡΠ΅ΡΠΎ Π½Π° ΡΠΎΠΏΠΎΠ³ΡΠ°ΡΠΈΡΠ°ΡΠ° Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½ΠΈΡΠ΅; ΠΠΎΡΡΠ°Π²ΡΠ²Π°ΡΠ΅ Π½Π° ΠΌΠ΅ΡΠ½ΠΈΠΎΡ ΠΏΡΠΈΠΌΠ΅ΡΠΎΠΊ; ΠΠΎΡΡΠ°Π²ΡΠ²Π°ΡΠ΅ Π½Π° ΠΌΠ΅ΡΠ΅Π½ ΠΊΠΎΠΎΡΠ΄ΠΈΠ½Π°ΡΠΎΠ½ ΡΠΈΡΡΠ΅ΠΌ ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ²Π°ΡΠ΅ ΠΏΡΠ°Π²ΡΠΈ Π·Π° ΠΈΠ·Π²Π΅Π΄ΡΠ²Π°ΡΠ΅ Π½Π° ΠΌΠ΅ΡΠ΅ΡΠ°ΡΠ°; ΠΠ΅ΡΠΈΠ½ΠΈΡΠ°ΡΠ΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Π½ΠΈΡΠ΅ ΠΌΠ΅ΡΠ½ΠΈ ΡΡΠ»ΠΎΠ²ΠΈ ΠΏΡΠΈ 2Π ΠΌΠ΅ΡΠ΅ΡΠ°ΡΠ°; ΠΠΎΠ·ΠΈΡΠΈΠΎΠ½ΠΈΡΠ°ΡΠ΅ Π½Π° ΡΠΈΡΠ°ΡΠΎΡ Π²ΡΠ· ΠΌΠ΅ΡΠ½Π°ΡΠ° ΠΏΠΎΠ²ΡΡΠΈΠ½Π°; ΠΠ»ΠΈΡΠ°Π½ΠΈΠ΅ Π½Π° Π»ΠΈΠ·Π³Π°ΡΠΎΡ ΠΈ Π½Π° Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ°ΡΠ° Π½Π° ΠΌΠ΅ΡΠ½Π°ΡΠ° ΠΈΠ³Π»Π° ΠΏΡΠΈ ΠΊΠΎΠΏΠΈΡΠ°ΡΠ΅ΡΠΎ Π½Π° ΡΠΎΠΏΠΎΠ³ΡΠ°ΡΠΈΡΠ°ΡΠ° Π½Π° ΠΏΠΎΠ²ΡΡΠΈΠ½ΠΈΡΠ΅; ΠΠΎΠ½ΡΡΠΎΠ»Π° Π½Π° ΡΠΎΡΡΠΎΡΠ±Π°ΡΠ° Π½Π° ΡΠ°Π΄ΠΈΡΡΠΎΡ Π½Π° ΠΌΠ΅ΡΠ½Π°ΡΠ°Π° ΠΈΠ³Π»Π°. ΠΠ΅ΡΠΎΡΠΌΠ°ΡΠΈΡΠ° Π½Π° ΠΌΠ΅ΡΠ΅Π½Π°ΡΠ° ΠΏΠΎΠ²ΡΡΠΈΠ½Π° (Π‘ΡΠ°ΡΠΈΡΠΊΠΈ ΠΈ ΠΠΈΠ½Π°ΠΌΠΈΡΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»); ΠΠ»ΠΈΡΠ°Π½ΠΈΠ΅ Π½Π° ΡΠ΅ΠΌΠΏΠ»ΠΈΡΠ°ΡΠΊΠ°ΡΠ° Π±ΡΠ·ΠΈΠ½Π°, ΡΠ΅ΠΌΠΏΠ»ΠΈΡΠ°ΡΠΊΠΎΡΠΎ ΡΠ°ΡΡΠΎΡΠ°Π½ΠΈΠ΅ ΠΈ Π½Π° Π²ΠΊΡΠΏΠ½Π°ΡΠ° ΠΌΠ΅ΡΠ½Π° Π΄ΠΎΠ»ΠΆΠΈΠ½Π°; ΠΠ»ΠΈΡΠ°Π½ΠΈΠ΅ Π½Π° Π³ΠΎΠ»Π΅ΠΌΠΈΠ½Π°ΡΠ° Π½Π° ΡΠ°Π΄ΠΈΡΡΠΎΡ Π½Π° Π·Π°ΠΎΠ±Π»ΡΠ²Π°ΡΠ΅ Π½Π° Π²ΡΠ²ΠΎΡ ΠΎΠ΄ ΠΌΠ΅ΡΠ½Π°ΡΠ° ΠΈΠ³Π»Π° ΠΈ Π½Π° ΡΠΎΠΎΠ΄Π½ΠΎΡΠΎΡ ΠΏΠΎΠΌΠ΅ΡΡ ΠΌΠ΅ΡΠ½Π°ΡΠ° ΡΠΈΠ»Π° ΠΈ Π±ΡΠ·ΠΈΠ½Π°ΡΠ° Π½Π° ΠΌΠ΅ΡΠ΅ΡΠ΅; ΠΠ»ΠΈΡΠ°Π½ΠΈΠ΅ Π½Π° ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈΡΠ΅ ΠΈΠ° ΠΏΡΠΈΠΌΠ΅Π½Π΅ΡΠΈΠΎΡ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΎΡ ΠΈ ΠΏΠ° ΡΡΠ΅ΠΊΠ²Π΅Π½ΡΠΈΡΠ°ΡΠ° Π½Π° ΡΠ½ΠΈΡΡΠΎΠΈΠ΄Π½Π½ΠΈΠΎΡ ΡΠΈΠ³Π½Π°Π» Π²ΡΠ· ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈΡΠ΅ Π½Π° Π΄ΠΈΡΠ΅ΡΠ΅Π½ΡΠΈΡΠ°Π»Π½ΠΈΠΎΡ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΎΡ ΠΈ ΠΠ»ΠΈΡΠ°Π½ΠΈΠ΅ Π½Π° ΠΊΠ²Π°Π½ΡΠΈΠ·Π°ΡΠΈΡΠ°ΡΠ° Π½Π° Π°Π½Π°Π»ΠΎΠ³Π½ΠΈΠΎΡ ΡΠΈΠ³Π½Π°Π»; Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠΊΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈ Π½Π° ΡΠ°ΠΏΠ°Π²ΠΎΡΡ Π²ΠΎ ΠΠ Π΄ΠΎΠΌΠ΅Π½.
ΠΠ° Π΄ΠΈΡΠ°Π³Π½ΠΎΡΡΠΈΡΠΈΡΠ°ΡΠ΅ Π½Π° ΡΡΠ»ΠΎΠ²ΠΈΡΠ΅ ΠΏΡΠΈ ΠΊΠΎΠΈ ΡΠ΅ ΡΠΎΠ·Π΄Π°Π²Π° ΠΎΠ±ΡΠ°Π±ΠΎΡΠ΅Π½Π°ΡΠ° ΠΏΠΎΠ²ΡΡΠΈΠ½Π° ΡΠΎΠ·Π΄Π°Π΄Π΅Π½ Π΅ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³ ΡΠΈΡΡΠ΅ΠΌ Π·Π° ΡΠ»Π΅Π΄Π΅ΡΠ΅ Π½Π° ΡΡΠ»ΠΎΠ²ΠΈΡΠ΅ ΠΏΡΠΈ ΠΊΠΎΠΈ ΡΠ΅ ΠΈΠ·Π²Π΅Π΄ΡΠ²Π°Π°Ρ Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»Π½ΠΈΡΠ΅ ΠΈΡΡΡΠ°ΠΆΡΠ²Π°ΡΠ° Π½Π° ΠΏΡΠΎΡΠ΅ΡΠΎΡ Π½Π° ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠ° ΡΠΎ ΡΡΡΡΠΆΠ΅ΡΠ΅. ΠΡΠΏΠΎΡΠΈΡΠ΅ ΠΈ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ°ΡΠ° Π²ΠΎ ΠΏΡΠΎΡΠ΅ΡΠΎΡ Π½Π° ΡΠ΅ΠΆΠ΅ΡΠ΅ ΡΠ΅ ΠΎΠ΄Π±ΡΠ°Π½ΠΈ ΠΊΠ°ΠΊΠΎ ΠΈΠ½Π΄ΠΈΠΊΠ°ΡΠΎΡΠΈ Π·Π° ΡΠ»Π΅Π΄Π΅ΡΠ΅ Π½Π° ΠΏΠΎΡΠ°Π²Π°ΡΠ° Π½Π° Π²ΠΈΠ±ΡΠ°ΡΠΈΠΈ ΠΈ Π²Π»ΠΈΡΠ°Π½ΠΈΡΠ°ΡΠ° Π·Π° ΠΏΠΎΡΠ°Π²Π° Π½Π° Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠΊΠΈΡΠ΅ ΠΎΡΡΡΠ°ΠΏΡΠ²Π°ΡΠ°.
ΠΠΎΡΠ΅Π±Π½ΠΎ ΠΌΠ΅ΡΡΠΎ Π΅ ΠΏΠΎΡΠ²Π΅ΡΠ΅Π½ΠΎ Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ°ΡΠ° Π·Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ²Π°ΡΠ΅ Π½Π° ΠΌΠ΅ΡΠ½Π°ΡΠ° Π½Π΅ΠΎΠ΄ΡΠ΅Π΅Π΄Π½ΠΎΡΡ Π½Π° ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈΡΠ΅ ΠΎΠ΄ ΠΌΠ΅ΡΠ΅ΡΠ΅ΡΠΎ Π½Π° ΡΠ°ΠΏΠ°Π²ΠΎΡΡΠ° ΡΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π° ΠΈΠ° ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΈ ΠΌΠ΅ΡΠ½ΠΈ ΡΡΠ΅Π΄ΠΈ. ΠΠΎ Π°Π½Π°Π»ΠΈΠ·Π°ΡΠ° Π΅ Π²ΠΊΠ»ΡΡΠ΅Π½Π° ΠΏΡΠΎΠ΄Π»Π°Π±ΠΎΡΡΠ½Π° ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡΠ° Π½Π° ΠΌΠΎΠΆΠ½ΠΈΡΠ΅ ΠΈΠ·Π²ΠΎΡΠΈ Π½Π° Π³ΡΠ΅ΡΠΊΠΈΡΠ΅ ΠΏΡΠΈ ΠΌΠ΅ΡΠ΅ΡΠ΅ Π½Π° ΡΠ°ΠΏΠ°Π²ΠΎΡΡΠ°, ΠΊΠΎΠΈ Π±ΠΈ ΡΡΠ΅Π±Π°Π»ΠΎ Π΄Π° ΡΠ΅ Π·Π΅ΠΌΠ°Π°Ρ Π²ΠΎ ΠΏΡΠ΅Π΄Π²ΠΈΠ΄ ΠΏΡΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ²Π°ΡΠ΅ΡΠΎ Π½Π° Π½Π΅ΠΎΠ΄ΡΠ΅Π΄Π΅Π½ΠΎΡΡΠ° Π½Π° ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈΡΠ΅, ΠΏΡΠ΅ΡΡΡΠ°Π²Π΅Π½ΠΈ ΡΠΎ Π΄ΠΈΡΠ°Π³ΡΠ°ΠΌΠΎΡ ΠΏΠ° ΠΡΠΈΠΊΠ°Π²Π°
Avoiding heavy computations in inverse calibration procedure for 7 DOF robot manipulator
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
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 machineβs 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
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/Β±45Λ)n], [(0/Β±30Λ)n] and [(0/Β±90Λ)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
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 PadenβKahan subproblem and its extension
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 systemsβopposite to conventional DenavitβHartenberg approach, where at least n ΓΎ 1 coordinate frames
are needed for a robot manipulator with n joints. The inverse kinematics solution in DenavitβHartenberg convention is
implicit. Instead, explicit solutions to inverse kinematics using the PadenβKahan subproblems could be expressed. This
article gives step-by-step application of geometric algorithm for the solution of all the cases of PadenβKahan 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
PadenβKahan 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, PadenβKahan subproblem, geometric algorithm, inverse kinematics, mathematical foundation
Influence of the Process Parameters on Laser - Assisted Automated Tape Placement Process
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
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%