Realising the open virtual commissioning of modular automation systems

To address the challenges in the automotive industry posed by the need to rapidly manufacture more product variants, and the resultant need for more adaptable production systems, radical changes are now required in the way in which such systems are developed and implemented. In this context, two enabling approaches for achieving more agile manufacturing, namely modular automation systems and virtual commissioning, are briefly reviewed in this contribution. Ongoing research conducted at Loughborough University which aims to provide a modular approach to automation systems design coupled with a virtual engineering toolset for the (re)configuration of such manufacturing automation systems is reported. The problems faced in the virtual commissioning of modular automation systems are outlined. AutomationML - an emerging neutral data format which has potential to address integration problems is discussed. The paper proposes and illustrates a collaborative framework in which AutomationML is adopted for the data exchange and data representation of related models to enable efficient open virtual prototype construction and virtual commissioning of modular automation systems. A case study is provided to show how to create the data model based on AutomationML for describing a modular automation system

Agile development for a multi-disciplinary bicycle stability test bench

Agile software development methods are used extensively in the software industry. This paper describes an argument to explain why these methods can be used within a multi-disciplinary project and provides a concrete description on how to implement such a method, using a case-study to support the rationale. The SOFIE (Intelligent Assisted Bicycle) project was created to develop mechatronic appliances to make bicycles more stable, i.e. safer. A bicycle stability test bench is created within this project and is used as the case study for this research. The relative complexity of the test bench development and partner structure within the SOFIE project has many similarities with large-scale complex projects found in industry. Thus it provides a good environment to research the application of Agile software methods to a multi-disciplinary project

Dealing with development risk and complexity in planning situations within product engineering processes

Every product development process is unique and individual. Nevertheless, patterns of recurring and similar elements exist in different processes which experience specific characteristics depending on the type of project. In addition to the different objectives that form the basis of a product development process, projects differ primarily in their share of new development and their degree of complexity. In order to deal appropriately with the resulting uncertainty, implementing agile approaches in processes of mechatronic system development is becoming more popular with the aim of making the development project more flexible. However, it must be borne in mind that not every development process requires an agile approach. Although plan-driven approaches have a poor ability to react to changes, they provide clear structure that leads to a common understanding of the process and a clear definition of objectives. Since a development project does not only contain problems that are well-suited for an agile or a sequential approach it is important to adapt the process to the underlying situation and requirements. In sufficiently plannable situations a purely agile approach would entail the loss of structure. On the other hand, a purely sequential approach for highly uncertain problems means that the process has to be adapted frequently in order to react appropriately to changes and newly acquired knowledge. The approach of ASD – Agile Systems design helps developers to implement suitable development procedures at different process levels depending on the degree of planning stability. In this context, this contribution presents a methodology that examines the influence of new development and complexity on different elements and supports developers in process planning by combining flexible and structuring elements to avoid multiple replanning

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems