Minimisation of energy consumption variance for multi-process manufacturing lines through genetic algorithm manipulation of production schedule

Typical manufacturing scheduling algorithms do not consider the energy consumption of each job, or its variance, when they generate a production schedule. This can become problematic for manufacturers when local infrastructure has limited energy distribution capabilities. In this paper, a genetic algorithm based schedule modification algorithm is presented. By referencing energy consumption models for each job, adjustments are made to the original schedule so that it produces a minimal variance in the total energy consumption in a multi-process manufacturing production line, all while operating within the constraints of the manufacturing line and individual processes. Empirical results show a significant reduction in energy consumption variance can be achieved on schedules containing multiple concurrent jobs

Data gathering and architecture aspects of a major EU wide energy efficiency project for SMEs

“Support and Training for an Excellent Energy Efficiency Performance” is a 3-year European project helping over 600 European cross-sector small and medium sized enterprises (SMEs) to reduce their energy use and become more energy-efficient. Companies participating in STEEEP benefit from tailored training and guidance on effective energy management tools and best practices provided by an established network of energy advisors from Chambers of Commerce and Industry (CCIs) in 10 different countries. SMEs in many EU countries employ over 90% of the workforce, so improving the energy efficiency of EU SMEs is therefore compelling, with clear advantages for the European economy. Energy efficiency in SMEs previously received less attention than in larger companies, the public sector and dwellings. Previously, policymakers had little energy (and related) data for SMEs, making prioritising ways to support energy conservation difficult. In addition staffing resources and knowledge levels within SMEs frequently determine the level of commitment to energy efficiency and implementing EU energy and climate policy, with a dedicated or even part time energy manager for many SMEs a rarity. The STEEEP project aims to help this by introducing training to SMEs via CCIs, and monitoring savings and providing feedback to SMEs. Crucial to this is the benchmarking of energy use: Basic data about the SMEs, the SME’s energy consumption, and information about the SME policies and procedures relating to energy were gathered form each of the over 600 participants. Managing these data is a considerable task, notably in several languages, using combinations of numeric, free text and other data, gathered through questionnaires. It is not merely fiscal metering data, and supporting information that are gathered, we ask for from occupancy, to building types, and to complete the energy management matrix. We describe how this is done; the data processing . survey design, initial data gathering, benchmarking, and database architecture. Energy use is gathered as the project progresses , with interventions and changes captured. This paper describes the methods used and presents lessons learnt. This include the process of collecting , storing and analyzing the data from over 600 SMEs in 10 different countries. It identifies how barriers were overcome and how information from the data collection is being used by Chambers of Commerce and Industry to help reduce energy use of SME

An exergy based method for resource accounting in factories

In the current global climate of declining fossil fuel reserves and due to the impact of industry on the natural environment, industrial sustainability is becoming ever more important. However, sustainability is quite a vague concept for many, and there are a range of interpretations of the word. If the resource efficiency of a factory is taken as a measure of its sustainability, then the concept becomes better defined and quantifiable. In order to analyse the resource efficiency of a factory and suggest improvements, all flows through the manufacturing system need to be modelled. However the factory is a complex environment, there is a wide variation in the quality levels of energy as well as the composition of material flows in the system. The research presented in this thesis shows how the thermodynamics-based concept of ‘exergy’ can be used to quantify the resource efficiency of a factory. The factory is considered an ‘integrated system’, meaning it is composed of the building and the production processes, both interacting with each other. This is supported by three case studies in different industries that demonstrate the practical application of the approach. A review of literature identified that it was appropriate to develop a novel approach that combined exergy analysis with the integrated view of the factory. Such an approach would allow a ‘holistic’ assessment of resource efficiency for different technology options possibly employable. The development of the approach and its illustration through practical case studies is the main contribution of the work presented. Three case studies, when viewed together, illustrate all aspects of the novel exergy based resource accounting approach. The first case study is that of an engine production line, in which the resource efficiency of this part of the factory is analysed for different energy system options relating to heating ventilation and air conditioning. Firstly, the baseline is compared with the use of a solar photovoltaic array to generate electricity, and then a heat recovery unit is considered. Finally, both of these options were used together, and here it is found that the non-renewable exergy supply and exergy destruction are reduced by 51.6% and 49.2% respectively. The second case study is that of a jaggery (a sugar substitute) production line. The exergy efficiency of the process is calculated based on varying the operating temperature of the jaggery furnace. The case study describes the modelling of al flows through the jaggery process in terms of exergy. Since this is the first example of an exergy analysis of a jaggery process, it can be considered a minor contribution of the work. An imaginary secondary process that could utilize the waste heat from the jaggery process is considered in order to illustrate the application of the approach to industrial symbiosis. The non-renewable exergy supply and exergy destruction are determined for the baseline and the alternative option. The goal of this case study is not to present a thermally optimized design; rather it illustrates how the exergy concept can be used to assess the impact of changes to individual process operations on the overall efficiency in industrial symbiosis. When considering natural resource consumption in manufacturing, accounting for clean water consumption is increasingly important. Therefore, a holistic methodology for resource accounting in factories must be able to account for water efficiency as well. The third case study is that of a food production facility where the water supply and effluent are modelled in terms of exergy. A review of relevant literature shows that previously, the exergy content of only natural water bodies and urban wastewater had been quantified. To the author’s knowledge, this is the first example of applying this methodology of modelling water flows in a manufacturing context. The results show that due to a high amount of organic content in food process effluent, there is significant recoverable exergy in it. Therefore, a hypothetical water treatment process was assumed to estimate the possible savings in exergy consumption. The results show that at least a net 4.1% savings in terms of exergy could be possible if anaerobic digestion water treatment was employed. This result can be significant for the UK since the food sector forms a significant portion of the industry in the country. Towards the end of the thesis, a qualitative study is also presented that aims to evaluate the practical utility of the approach for the industry. A mixed method approach was used to acquire data from experts in the field and analyse their responses. The exergy based resource accounting method developed in this thesis was first presented to them before acquiring the responses. A unanimous view emerged that the developed exergy based factory resource accounting methodology has good potential to benefit industrial sustainability. However, they also agreed that exergy was too complex a concept to be currently widely applied in practice. To this effect, measures that could help overcome this barrier to its practical application were presented which form part of future work.KAP project (knowledge awareness and prediction of man, machine material and methods in manufacturing) which received funding from the European Community's Seventh Framework Programme (FP7/2007 e 2013) under grant agreement no. 26011

Minimisation of Energy Consumption Variance in Manufacturing through Production Schedule Manipulation

In the manufacturing sector, despite the vital role it plays, the consumption of energy is rarely considered as a manufacturing process variable during the scheduling of production jobs. Due to both physical and contractual limits, the local power infrastructure can only deliver a finite amount of electrical energy at any one time. As a consequence of not considering the energy usage during the scheduling process, this limited capacity can be inefficiently utilised or exceeded, potentially resulting in damage to the infrastructure. To address this, this thesis presents a novel schedule optimisation system. Here, a Genetic Algorithm is used to optimise the start times of manufacturing jobs such that the variance in production line energy consumption is minimised, while ensuring that typical hard and soft schedule constraints are maintained. Prediction accuracy is assured through the use of a novel library-based system which is able to provide historical energy data at a high temporal granularity, while accounting for the influence of machine conditions on the energy consumption. In cases where there is insufficient historical data for a particular manufacturing job, the library-based system is able to analyse the available energy data and utilise machine learning to generate temporary synthetic profiles compensated for probable machine conditions. The performance of the entire proposed system is optimised through significant experimentation and analysis, which allows for an optimised schedule to be produced within an acceptable amount of time. Testing in a lab-based production line demonstrates that the optimised schedule is able to significantly reduce the energy consumption variance produced by a production schedule, while providing a highly accurate prediction as to the energy consumption during the schedules execution. The proposed system is also demonstrated to be easily expandable, allowing it to consider local renewable energy generation and energy storage, along with objectives such as the minimisation of peak energy consumption, and energy drawn from the National Grid

Proceedings of 8th International Conference Improving Energy Efficiency in Commercial Buildings (IEECB’14)

This book contains the proceedings of the 8th International Conference on Energy Efficiency in Commercial Buildings which took place in Frankfurt, Germany 1-3 April 2014. The IEECB conference brings together all the key players from this sector, including commercial buildings’ investors and property managers, energy efficiency experts and building technologies researchers, equipment manufacturers, service providers (ESCOs, utilities, facilities management companies) and policy makers, with a view to exchange information, to learn from each other and to network. The wide scope of topics covered during the IEECB’14 conference includes: smart building and low energy buildings, (Nearly) Net Zero Energy Buildings, equipment and systems (lighting, HVAC auxiliary equipment, ICT & office equipment, miscellaneous equipment, BEMS, electricity on-site production, renewable energies, etc.) and the latest advances in energy efficiency programmes, regulation & policies for public and private sector commercial buildings. Potential readers who may benefit from this book include researchers, engineers, policymakers, energy agencies, electric utilities, and all those who can influence the design, selection, application, and operation of electrical motor driven systems.JRC.F.7-Renewables and Energy Efficienc