Using formal methods to scope performance challenges for Smart Manufacturing Systems: focus on agility.

Smart Manufacturing Systems (SMS) need to be agile to adapt to new situations by using detailed, precise, and appropriate data for intelligent decision-making. The intricacy of the relationship of strategic goals to operational performance across the many levels of a manufacturing system inhibits the realization of SMS. This paper proposes a method for identifying what aspects of a manufacturing system should be addressed to respond to changing strategic goals. The method uses standard modeling techniques in specifying a manufacturing system and the relationship between strategic goals and operational performance metrics. Two existing reference models related to manufacturing operations are represented formally and harmonized to support the proposed method. The method is illustrated for a single scenario using agility as a strategic goal. By replicating the proposed method for other strategic goals and with multiple scenarios, a comprehensive set of performance challenges can be identified.

Sustainability Characterization for Additive Manufacturing.

Additive manufacturing (AM) has the potential to create geometrically complex parts that require a high degree of customization, using less material and producing less waste. Recent studies have shown that AM can be an economically viable option for use by the industry, yet there are some inherent challenges associated with AM for wider acceptance. The lack of standards in AM impedes its use for parts production since industries primarily depend on established standards in processes and material selection to ensure the consistency and quality. Inability to compare AM performance against traditional manufacturing methods can be a barrier for implementing AM processes. AM process sustainability has become a driver due to growing environmental concerns for manufacturing. This has reinforced the importance to understand and characterize AM processes for sustainability. Process characterization for sustainability will help close the gaps for comparing AM performance to traditional manufacturing methods. Based on a literature review, this paper first examines the potential environmental impacts of AM. A methodology for sustainability characterization of AM is then proposed to serve as a resource for the community to benchmark AM processes for sustainability. Next, research perspectives are discussed along with relevant standardization efforts.

Software Architecture for a Virtual Environment for Nano Scale Assembly (VENSA).

A Virtual Environment (VE) uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. The information flow between the user and the VE is bidirectional and the user can influence the environment. The software development of a VE requires orchestrating multiple peripherals and computers in a synchronized way in real time. Although a multitude of useful software components for VEs exists, many of these are packaged within a complex framework and can not be used separately. In this paper, an architecture is presented which is designed to let multiple frameworks work together while being shielded from the application program. This architecture, which is called the Virtual Environment for Nano Scale Assembly (VENSA), has been constructed for interfacing with an optical tweezers instrument for nanotechnology development. However, this approach can be generalized for most virtual environments. Through the use of VENSA, the programmer can rely on existing solutions and concentrate more on the application software design.

Virtual Environment for Manipulating Microscopic Particles With Optical Tweezers.

In this paper, virtual reality techniques are used to define an intuitive interface to a nanoscale manipulation device. This device utilizes optical methods to focus laser light to trap and reposition nano-to-microscopic particles. The underlying physics are simulated by the use of Lagrange mechanics. A unique control method for the manipulation of the particles is also provided. The user can naturally grab and steer the particles. Behind the scene, a complex computation is performed to find the new location of the potential field induced by the laser beam that would move the particles accordingly. Haptic feedback is used to constrain the steering motion within the physical capability of the potential field.