Dados do Empregador:
Referência da Vaga: BE-2019-069KUL
País: Bélgica
Empresa / Universidade: Flanders Make
Serviços / Produtos: Research for the manufacturing industry
No de Empregados: 100
Local de Trabalho: Leuven
Horas Trabalhadas por Semana: 38
Horas Trabalhadas por Dia: 7.6
Aeroporto Internac. Mais Próximo: Brussels
Transporte Público Mais Próximo:
Perfil do Estudante:
Faculdade: Electrical Engineering
Faculdade 2: Electronics
Faculdade 3: Mechanical Engineering
Faculdade 4: Mechatronics
Outra faculdade: Robotics
Nível de Estudo: Final do Curso
Study Level: End - (7 and more semesters)
Sexo Permitido:
Experiência anterior requerida: Outstanding student required
Outros Requisitos: • Result oriented, responsible and proactive; • A good communicator, able to communicate in English; • Eager to learn and a team player. Student status obligatory: please include a Certificate of Enrolment with your nomination. If trainee has non-EEA/Swiss nationality: maximum duration is 90 days.
Idioma 1: English
Nível de Idiomas: Avançado
Idioma 2:
Nível de Idiomas:
Idioma 3:
Nível de Idiomas:
Descritivo da Vaga:
Tipo de Atividade: Intuitive task scheduling and optimisation methodology for a two-armed collaborative robot Collaborative robots are relatively new in the industry, but they offer more flexibility than standard industrial robots. Therefore, they are well suited for assembly environments in which multiple product variants are to be assembled in small batch sizes. Typically this is done manually, but this limits throughput and puts high loads on the operators. Cobots could assist the human operators by taking over the highly repetitive, precise are heavy tasks, leaving the tasks with high variability and complexity up to the operator. An important barrier to deploy cobots in industry is the effort required for programming them for each product variant. Also task (re)scheduling between the operator is very important. Task scheduling methods should optimally allocate tasks to cobot and operators, according to their capabilities so that e.g. throughput is maximized while the operator load is not exceeding certain limits. Therefore a task scheduling methodology is needed which allows for intuitive (re)scheduling and both on- and offline optimization of loads: - Intuitive, because the operator should take the lead over the robot and tell the robot what to do. - Offline optimisation in terms of throughput and idle time, because the tasks need to be balanced between the human operator and the robot on beforehand. - Online optimisation, because the human operator might need to take over from the robot (i.e. due to a failed assembly step) and the work needs to be rescheduled. The goal of this internship is to develop a task (re)scheduling methodology which takes into account the nature of the tasks, the timings and the experience of the operator to optimise the scheduling towards idle time and throughput. The task scheduling algorithm should be able to run both offline and online and take into account the constraints from the operator. Of importance here is the intuitiveness of the interface/communication between the operator, the robot and the algorithm (i.e. vision, speech, gesture, etc.). The final validation will be on a two-armed robot in a collaborative set-up. Learning target : During the time of the internship you will learn about the complexities of human-robot collaboration in flexible assembly systems i.e. scheduling, communication, error handling, etc. You will extend your theoretical knowledge with practical experience in robotics.
Semanas oferecidas (mín.): 13
Semanas oferecidas (máx.): 26
Período de: 01/03/2019
até: 31/10/2019
Categoria: Pesquisa e Desenvolvimento
Moeda: EUR - Euro
Bolsa Auxílio: 200/Week
Refeitório na empresa ou vale refeição:
Deduções Esperadas: 0
Será Providenciada Por: IAESTE
Custo Estimado de Acomodação: 100/Week
Custo Estimado de Vida Incluindo Acomodação: 200/Week