Eeva Järvenpää

Process planning based on feature recognition method

Managing and controlling very complex manufacturing systems and vast volumes of accumulate knowledge, holonic manufacturing system is developed. This paper introduces a method, which utilizes feature-based modeling for defining a pre-process plan. The pre-process plan developed can be linked in a holonic system. This paper, the generic steps for making a product are called “pre-process plan”. The pre-process plan defines the required capabilities on a high level. All the resources have some sort of capability that represents the possible candidates for the product manufacturing. The feature recognition method offers geometric and non-geometric (such as shape, type, tolerance and material) information. Using feature information a pre-process plan can be defined. The fact that the pre-process plan does not strictly define the used processing methods allows the product to be manufactured on different machines based on their availability or other criteria. This is important in dynamic, adaptive production environment.

Presenting capabilities of resources and resource combinations to support production system adaptation

Todays turbulent production environment calls for adaptive and rapidly responding production systems that can adjust to required changes both in production capacity and processing functions. This kind of adaptivity can not be reached without intelligent methods and tools supporting the adaptation planning and deployment of the systems. This paper introduces novel method to present and manage capabilities of production resources and combined capabilities of multiple co-operating resources. This modeling approach enables matching of products and resources based on their required and provided capabilities and this way supports rapid allocation of resources.

Logistic and control aspects for flexible and reactive micro and desktop assembly at the factory level

In addition to micro assembly and micro manufacturing micro factories are currently widely studied around the world. However, the research is typically focusing on single machines and not so much on integration of single processes and machines into wider process chains and larger systems with integrated material logistics. This paper discusses issues related to realization of a larger scale integrated micro factory for assembly of multi-part products. Special attention is paid on the logistical aspects and control concepts supporting flexibility and dynamic reconfigurability of the system. A scenario of a microfactory system as a holonic manufacturing system enabling reactivity of the system to sudden changes and failure situations is also presented.

Formal resource and capability descriptions supporting rapid reconfiguration of assembly systems

Todays production environment is characterised by frequent changes in terms of high product variation, small batch sizes, high demand fluctuation as well as random unexpected disturbances on the factory floor. Production systems need to be rapidly reconfigurable and adaptable to these changing requirements. ReCaM project targets to develop a set of integrated tools for rapid and autonomous reconfiguration of production systems. Such tools need to be supported by formal information models describing the product requirements, as well as resource characteristics and functionalities. This paper concentrates on introducing the formal resource and capability models, which are used and further enriched to support ReCaM targets. Also examples of how these models can be applied to support rapid reconfiguration will be given.

Micro and Desktop Factories for Micro/Meso-Scale Manufacturing Applications and Future Visions

Micro and desktop factories are small-size production systems suitable for the manufacture of small products with micro and/or macro size features. The development originates in Japan, where small machines were developed in order to save resources when producing small products. In the late 1990’s, the research spread around the world, and since then multiple miniaturized production systems have been developed. However, the level of commercialization and industrial adoption is still relatively low and the breakthrough remains unseen. This paper discusses the potential application areas of micro- and desktop factory solutions. The research has been carried out as a mixed-method research combining extensive literature survey and 18 semi-structured interviews in Europe. The interviewees are both from academia and industry, including equipment and component providers, as well as users and potential users.

Dynamic operation environment — Towards intelligent adaptive production systems

Todays turbulent production environment calls for adaptive and rapidly responding production systems that can adjust to required changes in products, production volumes and unexpected failure situations. Holonic manufacturing systems aim to offer a solution for changeability requirements by providing self-organizing capabilities. This paper presents a concept of a holonic manufacturing framework and its implementation into a laboratory environment. The adaptivity of the presented holonic system rests on SOA-based communication and negotiation between entities through open interfaces, and matching of resource capabilities against product requirements.

Formal Information Model for Representing Production Resources

This paper introduces a concept and associated descriptions to formally describe physical production resources for modular and reconfigurable production systems. These descriptions are source of formal information for (automatic) production system design and (re-)configuration. They can be further utilized during the system deployment and execution. The proposed concept and the underlying formal resource description model is composed of three different description levels, namely Abstract Resource Description (ARD), Resource Description (RD) and Resource Instance Description (RID), each having different scope and objectives. This paper discusses in details the content and differences between these description levels.

Adaptation of Manufacturing Systems in Dynamic Environment Based on Capability Description Method

Nowadays manufacturing systems are characterized by constantly changing requirements caused by short lifecycle times of products, small batch sizes, increasing number of product variants and fast emergence of new technical solutions. Today’s turbulent production environment calls for adaptive and rapidly responding production systems that can adjust to required changes both in production capacity and processing functions. The European level strategic goal towards Competitive Sustainable Manufacturing (CSM) asks for the re-use and adaptation of production systems (Jovane et al., 2009). Adaptation allows users to utilize the full lifetime and potential of the systems and equipment and in this way supports the sustainability, both from economic and ecologic perspectives. However, in the previous projects (e.g. (Harms et al., 2008)), it has been recognized that, because of often expensive and inefficient adaptation process, companies rarely decide to adapt their production systems. This is mainly due lacking or insufficient information and documentation about the capabilities of the current system and its lifecycle, as well as lack of extensive methods to plan the adaptation. Today the adaptation of production systems is practically a human driven process, which relies strongly on the expertise of the system integrators or the end user of the system.

Towards Intelligent Assembly and Manufacturing Environment – Modular ICT Support for Holonic Manufacturing System

This paper discusses the possibilities of a modular and more transparent knowledge management concept for a holonic assembly and manufacturing environment that enhances representation of past and present status of the production system thus allowing autonomous reasoning to be applied. The modular ICT approach is developed for a holonic manufacturing system (HMS). The main characteristics of the system are that it is an open system and has characteristics of a complex system. The system itself is an adaptive system, where different services are needed depending on theevolution of the production system itself. The research approach represented here aims to enhance knowledge management and process control by facilitating the move from technology based solutions to conÞgurable systems and processes where the digital models and modular knowledge management systems can be conÞgured based on the need - not based on the closed legacy systems and Þxed process planning. The principles of modularization such as functionalities and interfaces, are used to deal with interactions of the full system.

Factory Level Logistics and Control Aspects for Flexible and Reactive Microfactory Concept

Micro assembly and micro manufacturing, as well as micro factories are currently widely studied around the world. However, the research is typically focusing on single machines and not so much on integration of single processes and machines into wider process chains and larger systems with integrated material logistics. This paper discusses issues related to the realization of a larger scale integrated micro factory for the assembly of multi-part products. Special attention is paid on the logistical aspects and control concepts supporting flexibility and dynamic reconfigurability of the system. A scenario of a microfactory system as a holonic manufacturing system enabling the reactivity to sudden changes and failure situations is also presented.