search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
Standards: OPC Machine Vision


@imveurope


www.imveurope.com


OPC UA vision interface to ease smart factory integration


Suprateek Banerjee, VDMA’s robotics and automation standards manager, updates on the OPC Machine Vision companion specification, designed to make vision interoperable with factory machines


‘W


ouldn’t it be great, if machines could communicate in a direct way with each other? Tis idea


is at the core of the Industry 4.0 movement to create the smart factory of the future,’ said Dr Horst Heinol-Heikkinen, chairman of VDMA’s OPC Machine Vision initiative and its working group. ‘Te goal of reaching interoperability is the


new core competence that must distinguish our future products in a connected world of Industrial IoT,’ continued Heinol-Heikkinen, who is also managing director of Asentics. ‘I am proud that machine vision plays a pioneering role and, as one of the first VDMA divisions, is presenting the release of an OPC UA companion specification to the public, thanks to extraordinary commitment and co-operation by core working group members who worked very hard and made it possible.’ Te VDMA, Europe’s biggest industrial


association of more than 3,200 firms from mechanical engineering and machine building, is driving the development of interoperability. It has teamed up with the OPC Foundation and its OPC UA technology, to develop market and industry-specific standards for the many domains in the sector, such as robotics, machine vision and machine tools. Tese domain-specific standards are companion specifications; part one of the machine vision specification has been published, and can be downloaded at OPC Foundation and VDMA Machine Vision websites.


Open platforms Te acronym OPC UA stands for Open Platform Communications Unified Architecture. OPC UA is a vendor and platform independent machine-to-machine communication technology, recommended by the German Industry 4.0 initiative and


other international consortiums, such as the Industrial Internet Consortium (IIC), to implement Industry 4.0. Te specification of OPC UA can be divided in two: the basis specification and companion specifications. Te basis specification describes how data can be transferred in an OPC UA manner, and the companion specifications describe what information and data are transferred. Te OPC Foundation is responsible for the development of the basis specification. Sector- specific companion specifications are developed in working groups, usually organised by trade associations, like the VDMA, a key player in the Industry 4.0 initiative. In early 2016, the VDMA


A trial


Machine Vision board decided to develop an OPC UA companion specification for machine vision. Te work has been carried out in the joint working group, made up of members from the OPC Foundation and VDMA Machine Vision. A core working group with 17 experts from leading European machine vision firms came up with proposals for the approach and contents, and monitored feedback from the wider machine vision sector. For broader reach, VDMA Machine Vision decided to bring this work into the G3 standardisation co-operation for machine vision.


abstracting the necessary behaviour via a state machine concept. A trial implementation was completed


and presented to an audience of automotive industry experts in May at an OPC UA automotive day in Wolfsburg. A hardware demonstrator is being developed, to be showcased at trade shows in Germany soon. In future parts of the standard, the generic


implementation has been completed and presented to automotive industry experts


basic information model will shiſt to a more specific skill-based information model. For this purpose, the proprietary input and output data black boxes will be broken down and substituted with standardised information structures and semantics. Tis follows the idea of implementing information model structures derived from OPC UA DI (device integration, part 100) as OPC Robotics has already done in part one of the OPC Robotics companion specification. Tus, it ensures the idea of cross domain interoperability, so that machine vision systems can talk to robots and vice versa – and, at a later stage, to all kinds of devices. Te official kick-off for part


two of the OPC Machine Vision companion specification began on 18 September, where all the members of the working group met at VDMA, Frankfurt to


brainstorm important topics to be covered in part two, and to lay a well-defined roadmap for the standard. Stefan Hoppe, president and executive


OPC Machine Vision part one Part one describes an abstraction of the generic vision system; a representation of a digital twin of the system. It handles the management of recipes, configurations and results in a standard way, whereas the contents stay vendor-specific and are treated as black boxes. It allows the control of a vision system in a general way,


36 Imaging and Machine Vision Europe • Yearbook 2019/2020


director of the OPC Foundation, said: ‘Machine vision has taken a decisive step into the Industry 4.0 era. Beyond the work done to adopt OPC UA as the interoperability platform for machine vision, we applaud the joint working group for embracing the spirit of inter-organisational collaboration on a global scale with G3. Tis big thinking aligns well with a key OPC Foundation focus on encouraging organisations to work together to reduce the vast number of overlapping custom information models into a harmonised set of OPC UA companion specifications which will benefit end-users and vendors by lowering barriers to true interoperability.’ O


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52