An investigation into minimising total energy consumption and total completion time in a flexible job shop for recycling carbon fiber reinforced polymer

The increased use of carbon fiber reinforced polymer (CFRP) in industry coupled with European Union restrictions on landfill disposal has resulted in a need to develop relevant recycling technologies. Several methods, such as mechanical grinding, thermolysis and solvolysis, have been tried to recover the carbon fibers. Optimisation techniques for reducing energy consumed by above processes have also been developed. However, the energy efficiency of recycling CFRP at the workshop level has never been considered before. An approach to incorporate energy reduction into consideration while making the scheduling plans for a CFRP recycling workshop is presented in this paper. This research sets in a flexible job shop circumstance, model for the bi-objective problem that minimise total processing energy consumption and makespan is developed. A modified Genetic Algorithm for solving the raw material lot splitting problem is developed. A case study of the lot sizing problem in the flexible job shop for recycling CFRP is presented to show how scheduling plans affect energy consumption, and to prove the feasibility of the model and the developed algorithm

A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the

Analysis of the “make or buy” decision process in a research and development sme

Start-up SMEs face various challenges and difficulties during their existence and due to their nature they often lack knowledge and resources to fully address these challenges. Unlike large companies which have access to various resources, those resources are a significant gap for SMEs and the business owners have to rely on their own limited knowledge. The “Make or buy” decision is a critical decision in an organisation. This decision can affect current and future costs, capability and competences in the company and by taking best practice approaches and measures towards the decision making, extensive costs can be potentially saved. In this study, literature best practices have been reviewed. In addition a small company has been studied and the current practices of the company have been compared to academic best practices. The result of the study will be used to improve the “Make or buy” decision process in the company

Understanding the role of protein misfolding in neurodegenerative diseases

Protein aggregates are hallmark of several age related disorders including neurodegenerative diseases such as Amyotrophic Lateral Sclerosis, Alzheimer’s and Parkinson’s disease. However, the underlying mechanisms by which these aggregated proteins impair cellular functions and cause toxicity is not clear. I will discuss efforts from my laboratory to characterize these misfolded and aggregated protein structures and their associated toxicity.https://digitalcommons.mtu.edu/techtalks/1040/thumbnail.jp

Optimal allocation of static and dynamic reactive power support for enhancing power system security

Power systems over the recent past few years, has undergone dramatic revolution in terms of government and private investment in various areas such as renewable generation, incorporation of smart grid to better control and operate the power grid, large scale energy storage, and fast responding reactive power sources. The ongoing growth of the electric power industry is mainly because of the deregulation of the industry and regulatory compliance which each participant of the electric power system has to comply with during planning and operational phase. Post worldwide blackouts, especially the year 2003 blackout in north-east USA, which impacted roughly 50 million people, more attention has been given to reactive power planning. At present, there is steady load growth but not enough transmission capacity to carry power to load centers. There is less transmission expansion due to high investment cost, difficulty in getting environmental clearance, and less lucrative cost recovery structure. Moreover, conventional generators close to load centers are aging or closing operation as they cannot comply with the new environmental protection agency (EPA) policies such as Cross-State Air Pollution Rule (CSAPR) and MACT. The conventional generators are getting replaced with far away renewable sources of energy. Thus, the traditional source of dynamic reactive power support close to load centers is getting retired. This has resulted in more frequently overloading of transmission network than before. These issues lead to poor power quality and power system instability. The problem gets even worse during contingencies and especially at high load levels. There is a clear need of power system static and dynamic monitoring. This can help planners and operators to clearly identify severe contingencies causing voltage acceptability problem and system instability. Also, it becomes imperative to find which buses and how much are they impacted by a severe contingency. Thus, sufficient static and dynamic reactive power resource is needed to ensure reliable operation of power system, during stressed conditions and contingencies. In this dissertation, a generic framework has been developed for filtering and ranking of severe contingency. Additionally, vulnerable buses are identified and ranked. The next task after filtering out severe contingencies is to ensure static and dynamic security of the system against them. To ensure system robustness against severe contingencies optimal location and amount of VAR support required needs to be found. Thus, optimal VAR allocation needs to be found which can ensure acceptable voltage performance against all severe contingency. The consideration of contingency in the optimization process leads to security constrained VAR allocation problem. The problem of static VAR allocation requirement is formulated as minlp. To determine optimal dynamic VAR installation requirement the problem is solved in dynamic framework and is formulated as a Mixed Integer Dynamic Optimization (MIDO). Solving the VAR allocation problem for a set of severe contingencies is a very complex problem. Thus an approach is developed in this work which reduces the overall complexity of the problem while ensuring an acceptable optimal solution. The VAR allocation optimization problem has two subparts i.e. interger part and nonlinear part. The integer part of the problem is solved by branch and bound (B&B) method. To enhance the efficiency of B&B, system based knowledge is used to customize the B&B search process. Further to reduce the complexity of B&B method, only selected candidate locations are used instead of all plausible locations in the network. The candidate locations are selected based upon the effectiveness of the location in improving the system voltage. The selected candidate locations are used during the optimization process. The optimization process is divided into two parts: static optimization and dynamic optimization. Separating the overall optimization process into two sub-parts is much more realistic and corresponds to industry practice. Immediately after the occurrence of the contingency, the system goes into transient (or dynamic) phase, which can extend from few milliseconds to a minute. During the transient phase fast acting controllers are used to restore the system. Once the transients die out, the system attains steady state which can extend for hours with the help of slow static controllers. Static optimization is used to ensure acceptable system voltage and system security during steady state. The optimal reactive power allocation as determined via static optimization is a valuable information. It\u27s valuable as during the steady state phase of the system which is a much longer phase (extending in hours), the amount of constant reactive power support needed to maintain steady system voltage is determined. The optimal locations determined during the static optimization are given preference in the dynamic optimization phase. In dynamic optimization optimal location and amount of dynamic reactive power support is determined which can ensure acceptable transient performance and security of the system. To capture the true dynamic behavior of the system, dynamic model of system components such as generator, exciter, load and reactive power source is used. The approach developed in this work can optimally allocate dynamic VAR sources. The results of this work show the effectiveness of the developed reactive power planning tool. The proposed methodology optimally allocates static and dynamic VAR sources that ensure post-contingency acceptable power quality and security of the system. The problem becomes manageable as the developed approach reduces the overall complexity of the optimization problem. We envision that the developed method will provide system planners a useful tool for optimal planning of static and dynamic reactive power support that can ensure system acceptable voltage performance and security

A review of information flow diagrammatic models for product-service systems

A product-service system (PSS) is a combination of products and services to create value for both customers and manufacturers. Modelling a PSS based on function orientation offers a useful way to distinguish system inputs and outputs with regards to how data are consumed and information is used, i.e. information flow. This article presents a review of diagrammatic information flow tools, which are designed to describe a system through its functions. The origin, concept and applications of these tools are investigated, followed by an analysis of information flow modelling with regards to key PSS properties. A case study of selection laser melting technology implemented as PSS will then be used to show the application of information flow modelling for PSS design. A discussion based on the usefulness of the tools in modelling the key elements of PSS and possible future research directions are also presented

Evaluation of the state-of-the-art in informatics in glucometers

This review evaluated the level of informatics in glucometers through an assessment of the quantity and types of information and advice provided to users. Manufacturer websites were investigated and the characteristics of glucometers were examined. One hundred glucometers from 27 manufacturers were analysed. Many glucometers contained simple informatics features and five also contained on-device graphing features for users to monitor trends. Some manufacturers have extended informatics via external software. A small number of glucometers provided knowledge for the user by, for example, simple embedded decision support protocols. However, it is suggested that glucometers could better serve as primary care devices through the incorporation of more decision support directly on the device

Requirements analysis for decision-support system design: evidence from the automotive industry

The purpose of this paper is to outline the requirements analysis that was carried out to support the development of a system that allows engineers to view real-time data integrated from multiple silos such as Product Lifecycle Management (PLM) and Warranty systems, in a single and visual environment. The outcome of this study provides a clear understanding of how engineers working in different phases of the product-lifecycle could utilise such information to improve the decision making process and as a result design better products. This study uses data collected via in-depth semi-structured interviews and workshops that includes people working in various roles within the automotive sector. In order to demonstrate the applicability this approach, SysML diagrams are also provided

Layout Optimization of a repair facility using discrete event simulation

Technological advancements in the field of simulation have enabled production managers to model and simulate their facilities under various scenarios, in order to optimize system performance. In particular the reconfiguration of factory layouts can be time consuming and expensive; Discrete Event Simulation (DES) can be used to model and assess various scenarios to assist production managers with layout planning. Significant benefits can be achieved through the use of DES for factory layout optimization including: decreased lead times, reduced manufacturing costs, efficient materials handling and increased profit. This paper presents the development of a DES model in WITNESS for the analysis and factory layout optimization of a repair facility. The aim of the model is to allow decision makers to assess various layouts and configurations with a view to optimize production. The model has been built with a link to an Excel spreadsheet to enable data input and the visualization of Key Performance Indicators (KPIs). Specific functions have been built into the simulation model to set and save new layouts within Excel to facilitate layout optimization. The model will be used to optimize the factory configuration

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets