This paper describes an agent-based software infrastructure for agile industrial production. This production is done on special devices called equiplets. A grid of these equiplets connected by a fast network is capable of producing a variety of different products in parallel. The multi-agent-based underlying systems uses two kinds of agents: an agent representing the product and an agent representing the equiplet.
MULTIFILE
This papers presents some ideas to use so-called software agents as a software representation of a product not only during manufacturing but also during the whole life cycle of the product. Software agents are autonomous entities capable of collecting useful information about products. By their design and capabilities software agents fit well in the concept of ubiquitous computing. We use these agents in our newly developed manufacturing process. This paper discusses further use of agent technology.
One of the major challenges for microsystem-based (MEMS -based) devices producing companies in general, and Bronkhorst High-Tech in particular, is to determine as early as possible in the production process which devices perform within specifications and if so by how much. Being able to separate the devices that do not comply as early as possible in the assembly flow would prevent spending time, money and materials on unsellable products. Being able to further separate good devices in multiple “performance bins” would bring even more cost and waste reduction by enabling Bronkhorst to pre-select finished products for different customer requirements. In this project we specifically focus on a micromachined flow sensor which is considered for a scale-up in production volumes in the near future. The ability to separate out badly performing devices translates to the challenge of finding a suitable test method, yielding the following research question: what are the success factors that would allow our MEMS partners to correlate product performance with measurements (tests) performed early in the production cycle? An answer makes it possible to implement the planned production scale-up of this MEMS device but also to reduce costs and waste typically associated with production failures. The device selected in this project is taken as an example for a broad range of chip-based MEMS devices with similar challenges. Therefore, we plan to use an applied research approach, looking at theoretical models of both device and production process, performing correlation measurements and delivering our recommendations on how to best tackle these production issues. It is our intention to thus generate expertise (knowledge & data) as well as a network on which we build a consortium around a future PPS (public-private partnership) where these challenges form a common theme.
