Challenges of cloud technology in manufacturing environment

The rapid growth Information systems and advanced network technologies have significant impact on enterprises around the world. Enterprises are trying to gain competitive advantage in open global markets by using the latest technologies, along with advanced networks, to create collaboration, reduce costs, and maximize productivity. The combination of latest technologies and advanced manufacturing networks technologies lead to growth of new manufacturing model named Cloud Manufacturing which can shift the manufacturing industry from product-oriented manufacturing to services-oriented manufacturing. This paper explores the literature about the current Manufacturing problems, understands the concept of Cloud Computing Technology, introduces Cloud Manufacturing and its role in the enterprise, and investigates the obstacles and challenges of adopting Cloud Manufacturing in enterprises

Security aspects in cloud based condition monitoring of machine tools

In the modern competitive environments companies must have rapid production systems that are able to deliver parts that satisfy highest quality standards. Companies have also an increased need for advanced machines equipped with the latest technologies in maintenance to avoid any reduction or interruption of production. Eminent therefore is the need to monitor the health status of the manufacturing equipment in real time and thus try to develop diagnostic technologies for machine tools. This paper lays the foundation for the creation of a safe remote monitoring system for machine tools using a Cloud environment for communication between the customer and the maintenance service company. Cloud technology provides a convenient means for accessing maintenance data anywhere in the world accessible through simple devices such as PC, tablets or smartphones. In this context the safety aspects of a Cloud system for remote monitoring of machine tools becomes crucial and is, thus the focus of this pape

Online on-board optimization of cutting parameter for energy efficient CNC milling

Energy efficiency is one of the main drivers for achieving sustainable manufacturing. Advances in machine tool design have reduced the energy consumption of such equipment, but still machine tools remain one of the most energy demanding equipment in a workshop. This study presents a novel approach aimed to improve the energy efficiency of machine tools through the online optimization of cutting conditions. The study is based on an industrial CNC controller with smart algorithms optimizing the cutting parameters to reduce the overall machining time while at the same time minimizing the peak energy consumption

Overview of Remaining Useful Life prediction techniques in Through-life Engineering Services

Through-life Engineering Services (TES) are essential in the manufacture and servicing of complex engineering products. TES improves support services by providing prognosis of run-to-failure and time-to-failure on-demand data for better decision making. The concept of Remaining Useful Life (RUL) is utilised to predict life-span of components (of a service system) with the purpose of minimising catastrophic failure events in both manufacturing and service sectors. The purpose of this paper is to identify failure mechanisms and emphasise the failure events prediction approaches that can effectively reduce uncertainties. It will demonstrate the classification of techniques used in RUL prediction for optimisation of products’ future use based on current products in-service with regards to predictability, availability and reliability. It presents a mapping of degradation mechanisms against techniques for knowledge acquisition with the objective of presenting to designers and manufacturers ways to improve the life-span of components

Multi-capacity combinatorial ordering GA in application to cloud resources allocation and efficient virtual machines consolidation

This paper describes a novel approach making use of genetic algorithms to find optimal solutions for multi-dimensional vector bin packing problems with the goal to improve cloud resource allocation and Virtual Machines (VMs) consolidation. Two algorithms, namely Combinatorial Ordering First-Fit Genetic Algorithm (COFFGA) and Combinatorial Ordering Next Fit Genetic Algorithm (CONFGA) have been developed for that and combined. The proposed hybrid algorithm targets to minimise the total number of running servers and resources wastage per server. The solutions obtained by the new algorithms are compared with latest solutions from literature. The results show that the proposed algorithm COFFGA outperforms other previous multi-dimension vector bin packing heuristics such as Permutation Pack (PP), First Fit (FF) and First Fit Decreasing (FFD) by 4%, 34%, and 39%, respectively. It also achieved better performance than the existing genetic algorithm for multi-capacity resources virtual machine consolidation (RGGA) in terms of performance and robustness. A thorough explanation for the improved performance of the newly proposed algorithm is given

Multi criteria supplier selection from social aspects in Thai tyre rubber industry

One of the main issues for companies and organisations is choosing the most appropriate supplier regarding social issues. Besides traditional criteria, companies started to focus on social issues in supplier selection. The methods of group decision making are well established approaches to tackle this issue which could allow decision makers to determine socially selected suppliers' problems. Many existing researches, nonetheless, encompasses scant review of ambiguity which is involved in the process of selecting suppliers. Hence, this study aims to propose a method combines the strength of the Fuzzy sets to deal with an uncertainty or vagueness with AHP-TOPSIS approach to select suppliers by concerning social aspects. AHP method used to identify criteria weights and TOPSIS approach is utilized to sort and select the best appropriate supplier. According to the literature review and company requirements, the criteria in social perspectives was developed to eight criteria. This study uses the questionnaire to gather data from top five manager's judgements who had been chosen based on purpose and self-selection sampling in each department. A case study was carried out in Thailand in the Tyre rubber sector to validate result. The findings demonstrate that Job security (34%) is the most important criteria, following by Employees' health and safety (16%) and Training programs (12%) respectively. The study also presents that "Supplier D" is the most suitable supplier above other suppliers

The effect of time pressure on the performance of dexterous operations

This study explores the effects of time pressure in dexterous operations on two types of interface: the fixed interface and the moving interface. Results show that the accuracy of finger movement is decreased, the information processing on the sense of sequence, position and direction is worsened by the psychological disturbance. The findings indicate that a fixed interface is more robust to performance and participants can learn and perform tasks quicker than a moving interface. Finally, the researchers give some practices on both fixed and moving interface design

Development of an ontology for aerospace engine components degradation in service

This paper presents the development of an ontology for component service degradation. In this paper, degradation mechanisms in gas turbine metallic components are used for a case study to explain how a taxonomy within an ontology can be validated. The validation method used in this paper uses an iterative process and sanity checks. Data extracted from on-demand textual information are filtered and grouped into classes of degradation mechanisms. Various concepts are systematically and hierarchically arranged for use in the service maintenance ontology. The allocation of the mechanisms to the AS-IS ontology presents a robust data collection hub. Data integrity is guaranteed when the TO-BE ontology is introduced to analyse processes relative to various failure events. The initial evaluation reveals improvement in the performance of the TO-BE domain ontology based on iterations and updates with recognised mechanisms. The information extracted and collected is required to improve service k nowledge and performance feedback which are important for service engineers. Existing research areas such as natural language processing, knowledge management, and information extraction were also examined

Degradation assessment of industrial composites using thermography

Thermographic inspection is a relatively new technique for Non-Destructive Testing (NDT) which has been gathering increasing interest due to its relatively low cost hardware and extremely fast data acquisition properties. This technique is especially promising in the area of rapid automated damage detection and quantification. In collaboration with a major industry partner from the aerospace sector advanced thermography-based NDT software for impact damaged composites is introduced. The software is based on correlation analysis of time-temperature profiles in combination with an image enhancement process. The prototype software is aiming to a) better visualise the damages in a relatively easy-to-use way and b) automatically and quantitatively measure the properties of the degradation. Knowing that degradation properties play an important role in the identification of degradation types, tests and results on specimens which were artificially damaged have been performed and analyzed.EPSR

Service Knowledge Capture and Reuse

The keynote will start with the need for service knowledge capture and reuse for industrial product-service systems. A novel approach to capture the service damage knowledge about individual component will be presented with experimental results. The technique uses active thermography and image processing approaches for the assessment. The paper will also give an overview of other non-destructive inspection techniques for service damage assessment. A robotic system will be described to automate the damage image capture. The keynote will then propose ways to reuse the knowledge to predict remaining life of the component and feedback to design and manufacturing