Computer aided inspection procedures to support smart manufacturing of injection moulded components

This work presents Reverse Engineering and Computer Aided technologies to improve the inspection of injection moulded electro-mechanical parts. Through a strong integration and automation of these methods, tolerance analysis, acquisition tool-path optimization and data management are performed. The core of the procedure concerns the automation of the data measure originally developed through voxel-based segmentation. This paper discusses the overall framework and its integration made according to Smart Manufacturing requirements. The experimental set-up, now in operative conditions at ABB SACE, is composed of a laser scanner installed on a CMM machine able to measure components with lengths in the range of 5÷250 mm, (b) a tool path optimization procedure and (c) a data management both developed as CAD-based applications

A question of trust: can we build an evidence base to gain trust in systematic review automation technologies?

Background Although many aspects of systematic reviews use computational tools, systematic reviewers have been reluctant to adopt machine learning tools. Discussion We discuss that the potential reason for the slow adoption of machine learning tools into systematic reviews is multifactorial. We focus on the current absence of trust in automation and set-up challenges as major barriers to adoption. It is important that reviews produced using automation tools are considered non-inferior or superior to current practice. However, this standard will likely not be sufficient to lead to widespread adoption. As with many technologies, it is important that reviewers see “others” in the review community using automation tools. Adoption will also be slow if the automation tools are not compatible with workflows and tasks currently used to produce reviews. Many automation tools being developed for systematic reviews mimic classification problems. Therefore, the evidence that these automation tools are non-inferior or superior can be presented using methods similar to diagnostic test evaluations, i.e., precision and recall compared to a human reviewer. However, the assessment of automation tools does present unique challenges for investigators and systematic reviewers, including the need to clarify which metrics are of interest to the systematic review community and the unique documentation challenges for reproducible software experiments. Conclusion We discuss adoption barriers with the goal of providing tool developers with guidance as to how to design and report such evaluations and for end users to assess their validity. Further, we discuss approaches to formatting and announcing publicly available datasets suitable for assessment of automation technologies and tools. Making these resources available will increase trust that tools are non-inferior or superior to current practice. Finally, we identify that, even with evidence that automation tools are non-inferior or superior to current practice, substantial set-up challenges remain for main stream integration of automation into the systematic review process

Intelligent Automation Technologies for Machine Tool Industry

Chapter Two, Automation Door Planning Book, Executive Yuan Secretary Ministry of Science and Engineering, China, 201

Supporting Knitwear Design Using Case-Based Reasoning

Organised by: Cranfield UniversityKnitwear design is a creative activity that is hard to automate using the computer. The production of the associated knitting pattern, however, is repetitive, time-consuming and error-prone, calling for automation. Our objectives are two-fold: to facilitate the design and to ease the burden of calculations and checks in pattern production. We conduct a feasibility study for applying case-based reasoning in knitwear design: we describe appropriate methods and show how they can be implemented.Mori Seiki – The Machine Tool Compan

Cognitive consequences of clumsy automation on high workload, high consequence human performance

The growth of computational power has fueled attempts to automate more of the human role in complex problem solving domains, especially those where system faults have high consequences and where periods of high workload may saturate the performance capacity of human operators. Examples of these domains include flightdecks, space stations, air traffic control, nuclear power operation, ground satellite control rooms, and surgical operating rooms. Automation efforts may have unanticipated effects on human performance, particularly if they increase the workload at peak workload times or change the practitioners' strategies for coping with workload. Smooth and effective changes in automation requires detailed understanding of the congnitive tasks confronting the user: it has been called user centered automation. The introduction of a new computerized technology in a group of hospital operating rooms used for heart surgery was observed. The study revealed how automation, especially 'clumsy automation', effects practitioner work patterns and suggest that clumsy automation constrains users in specific and significant ways. Users tailor both the new system and their tasks in order to accommodate the needs of process and production. The study of this tailoring may prove a powerful tool for exposing previously hidden patterns of user data processing, integration, and decision making which may, in turn, be useful in the design of more effective human-machine systems

An automated Model-based Testing Approach in Software Product Lines Using a Variability Language.

This paper presents the application of an automated testing approach for Software Product Lines (SPL) driven by its state-machine and variability models. Context: Model-based testing provides a technique for automatic generation of test cases using models. Introduction of a variability model in this technique can achieve testing automation in SPL. Method: We use UML and CVL (Common Variability Language) models as input, and JUnit test cases are derived from these models. This approach has been implemented using the UML2 Eclipse Modeling platform and the CVL-Tool. Validation: A model checking tool prototype has been developed and a case study has been performed. Conclusions: Preliminary experiments have proved that our approach can find structural errors in the SPL under test. In our future work we will introduce Object Constraint Language (OCL) constraints attached to the input UML mode

Techno-Economic Analysis of Hybrid Layered Manufacturing

Subtractive manufacturing (CNC machining) has high quality of geometric and material properties but is slow, costly and infeasible in some cases; additive manufacturing (RP) is just the opposite. Total automation and hence speed is achieved in RP by compromising on quality. Hybrid Layered Manufacturing (HLM) developed at IIT Bombay combines the best features of both these approaches. It uses arc welding for building near-net shapes which are finish machined to final dimensions. High speed of HLM surpasses all other processes for tool making by eliminating NC programming and rough machining. The techno-economic viability of HLM process has been proved through a real life case study. Time and cost of tool making using HLM promises to be substantially lower than that of CNC machining and other RP methods. Interestingly, the material cost in HLM was also found to be lower. HLM is a cheaper retrofitment to any 3 or 5 axis CNC milling machine or machining center.Mechanical Engineerin

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