Scheduling of Machine Startup and Shutdown to Reduce Energy Consumption in Bernoulli Production Lines

2012 ◽  
Author(s):  
Guorong Chen ◽  
Liang Zhang ◽  
Jorge Arinez ◽  
Stephan Biller
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Production Systems ◽  
Numerical Study ◽  
Effective Control ◽  
Efficient Production ◽  
Reliability Model ◽  
Production Lines ◽  
Finite Buffers ◽  
Automotive Paint

Effective control of production operations usually leads to improved energy efficiency in manufacturing systems. In this paper, we investigate energy consumption reduction in production systems by scheduling of machine startup and shutdown. Specifically, we consider serial production lines with finite buffers and machines having Bernoulli reliability model. This machine reliability model is applicable in production situations, where the downtime is relatively short and comparable to machine cycle time (e.g., automotive paint shops and general assembly). Using transient analysis of the systems at hand, an analytical performance evaluation technique is developed for Bernoulli serial lines with time-dependent machine efficiencies. In addition, trade-off between productivity and energy-efficiency in production systems is discussed and the energy-efficient production problem is formulated as a constrained optimization problem. The effects and practical implications of operations schedule are demonstrated using a numerical study on automotive paint shop operations.

scholarly journals Computer Scenario-Precedent Technology Treining of Energy Managers

2021 ◽  
Vol 43 (3) ◽  
pp. 75-86
Author(s):  
B.M. Pleskach ◽  
◽  
V.D. Samoilov ◽  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Production Systems ◽  
Topical Issue ◽  
Scenario Modeling ◽  
Industrial Enterprises ◽  
Stationary Energy ◽  
Software Modules ◽  
Energy Manager ◽  
Theoretical Foundations

The article considers the topical issue of developing simulators for advanced training of specialists in energy efficiency management of industrial enterprises and utilities. The aim of the study is to develop the theoretical foundations of the use of computerized systems for training energy managers. The object of the study is the practical activities of the personnel of the enterprise, aimed at improving the energy efficiency of production systems for various purposes. The research method based on scenario modeling of energy manager actions and precedent modeling of equipment reactions to such actions. The modeling of energy manager actions based on the Deming cycle, and the modeling of reactions of production systems based on cases of quasi-stationary energy consumption of the technologi-cal system. The software platform of the proposed technology consists of a base of precedents for quasistationary energy consumption and software modules that reproduce the PDCA control cycle (Plen-Do-Check-Act). The technology allows to work out the actions of the energy manager aimed at planning energy saving measures and calculating the financial and economic results achieved during their implementation.

IoT Based Energy Efficiency Monitoring in Stamping Workshop

2020 ◽  
Author(s):  
L. Gan ◽  
W. Xiong ◽  
L. Li ◽  
L. Zhu ◽  
H. Huang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Data Analysis ◽  
Data Storage ◽  
Energy Savings ◽  
Specific Energy Consumption ◽  
Efficient Production ◽  
Flow Energy ◽  
Wide Range ◽  
Analysis System

Abstract Stamping is employed in a wide range of applications including household appliances, automobiles, vessel, and aerospace. Due to the discrete flow energy-intensive processes and dynamic energy changes in stamping production, it has great potential for energy savings. There still lacks an effective method to monitor and analyze the energy efficiency in stamping workshop. To this end, this paper proposes an energy efficiency monitoring and analysis system based on Internet of Things (IoT). The characteristics in stamping workshop are first analyzed, the energy consumption is decomposed, and the makespan is quantified. Besides, energy efficiency indicators of energy efficiency in the press machine, specific energy consumption in the part, and energy efficiency in the workshop are analyzed and defined. Then the detailed information about the energy efficiency monitoring and analysis system as data acquisition, data transmission, data storage, data analysis, and display based on IoT is presented. Finally, a forklift stamping workshop was investigated to validate the effectiveness of the proposed method. The interface and the results of the data analysis showed that the proposed system can monitor the energy efficiency in the stamping workshop comprehensively. Furthermore, potential opportunities for energy consumption reduction and efficient production can be identified.

Ensemble Neural Network Model for Predicting the Energy Consumption of a Milling Machine

2015 ◽  
Author(s):  
Ronay Ak ◽  
Moneer M. Helu ◽  
Sudarsan Rachuri
Keyword(s):  
Energy Consumption ◽  
Prediction Model ◽  
Prediction Models ◽  
Production Systems ◽  
Face Milling ◽  
Model Parameters ◽  
Efficient Production ◽  
Milling Machine ◽  
Energy Prediction

Accurate prediction of the energy consumption is critical for energy-efficient production systems. However, the majority of existing prediction models aim at providing only point predictions and can be affected by uncertainties in the model parameters and input data. In this paper, a prediction model that generates prediction intervals (PIs) for estimating energy consumption of a milling machine is proposed. PIs are used to provide information on the confidence in the prediction by accounting for the uncertainty in both the model parameters and the noise in the input variables. An ensemble model of neural networks (NNs) is used to estimate PIs. A k-nearest-neighbors (k-nn) approach is applied to identify similar patterns between training and testing sets to increase the accuracy of the results by using local information from the closest patterns of the training sets. Finally, a case study that uses a dataset obtained by machining 18 parts through face-milling, contouring, slotting and pocketing, spiraling, and drilling operations is presented. Of these six operations, the case study focuses on face milling to demonstrate the effectiveness of the proposed energy prediction model.

Energy Consumption Reduction in Serial Production Lines via Controlled Machine Startup

2011 ◽  
Author(s):  
Guorong Chen ◽  
Liang Zhang ◽  
Jorge Arinez ◽  
Stephan Biller
Keyword(s):  
Energy Consumption ◽  
Capital Investment ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Production Lines ◽  
Energy Consumption Reduction ◽  
Consumption Reduction ◽  
Serial Production Lines

Research efforts for energy consumption reduction in manufacturing systems have been centered at technology and process innovation. These projects, however, often involve major capital investment of new equipment and material. In this paper, we explore energy saving opportunities through improvement in factory floor operations. Specifically, in the framework of Bernoulli serial lines, we consider production systems with stripping operations. In such systems, the in-process buffers have to be depleted at the end of each shift to avoid quality deterioration during off-shift periods. Transient analysis of the systems are carried out and formulas to calculate the performance measures are derived. In addition, we investigate the effect of machine startup schedule on the system performances and develop optimal startup schedule which, as shown in the paper, can lead to significant improvement in energy utilization efficiency.

Numerical study of the energy efficiency of the building envelope containing multi-alveolar structures under Tunisian weather conditions

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Nour Lajimi ◽  
Nour Ben Taher ◽  
Noureddine Boukadida
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Thermal Behavior ◽  
Thermal Insulation ◽  
Numerical Study ◽  
Thermal Inertia ◽  
Building Envelope ◽  
Winter Period ◽  
Alveolar Structure ◽  
Major Interest

Abstract The study of the thermal inertia of buildings is a subject of major interest. The thermal insulation and the nature of the wall sensitively modify the inertia of the building and are the solutions to improve the energy efficiency of the envelope. The roof is well exposed to solar radiation in summer and contributes to significant losses in winter due to convective exchanges. To lead to a thermal comfort, a thermal insulation is necessary. In this context, we carry out a numerical study of the thermal behavior of a building with two zones in variable meteorological conditions for a Tunisian climate (region of Sousse) based on the thermoelectric analogy and using the nodal method as a numerical method. The object of this work is to study the effect of the thermal inertia of the roof equipped with a multi-alveolar structure on the thermal behavior of the air inside the room and on its energy consumption. Taking into account the energy input of occupant, a complete model was established to increase the accuracy of the calculations. The results show that the multi-alveolar structure placed on the outside of the roof reduces energy consumption during the winter period when the alveolar structure is placed in the conductive direction and during the summer period when the alveolar structure is placed in the insulate direction.

scholarly journals Economic Energy Efficiency of Food Production Systems

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5826
Author(s):  
Bartłomiej Bajan ◽  
Aldona Mrówczyńska-Kamińska ◽  
Walenty Poczta
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Food Production ◽  
Food Industry ◽  
Energy Intensity ◽  
Production Systems ◽  
Developed Countries ◽  
Total Consumption ◽  
Global Increase ◽  
High Level

The current global population growth forecast carries with it a global increase in demand for food. In order to meet this demand, it is necessary to increase production, which requires an increase in energy consumption. However, forecasted energy production growth is insufficient and traditional sources of energy are limited; hence, it is necessary to strive for greater energy efficiency in food production systems. The study aimed to compare the economic energy efficiency of food production systems in selected countries and identify the sources of diversification in this field. As a measure of energy efficiency, the indicators of the energy intensity of food production were used in this study. To calculate these indicators, a method based on input-output life-cycle assessment assumptions was used, which enables researchers to obtain fully comparable results between countries. The study showed that despite an increase in energy consumption in the food production systems of the analyzed countries by an average of 27%, from 19.3 EJ to 24.5 EJ, from 2000 to 2014, their energy intensity decreased, on average, by more than 18%, from 8.5 MJ/USD to 6.9 MJ/USD. This means that energy efficiency improvements are possible even under conditions of increased energy consumption, which in turn, means that food production can increase significantly. In the case of developed countries, the main inefficiencies are found in agricultural production, while in developing countries, they are observed in the food industry. Decision-makers should also pay attention to the high level of energy intensity that results from the supply of inputs to agriculture and the food industry because there is great potential for the improvement of energy efficiency in this field, especially because energy consumption associated with supply constitutes a major part of total consumption in the food production systems of developed countries.

Ontology-Based Description of Energy Optimization Potentials for Production Environments

2015 ◽  
Vol 805 ◽  
pp. 53-60 ◽  
Author(s):  
Markus Brandmeier ◽  
Franziska Schäfer ◽  
Sven Kreitlein ◽  
Jörg Franke
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Product Life Cycle ◽  
Production Systems ◽  
Energy Optimization ◽  
Search Queries ◽  
Information Demand ◽  
Energy Consumption Optimization ◽  
Production Environments ◽  
New Business

Energy efficiency of production systems and of the product itself has grown to a critical competitive factor. Besides the manufacturer’s monetary motivation there are increasing incentives to meet customers’ expectations regarding lifecycle cost and the ecological footprint of products. That neo-ecology, as one megatrend, leads to a new business moral resulting in an energy optimization of the whole product life cycle in terms of resource and energy input. There is a plenty of measures to reduce the energy consumption of a production system and thus to increase its efficiency. To do so companies do not have to develop proprietary solutions for their production sites but can draw on a large pool of measures. However, in practice, many energy optimization measures are unknown to their energy managers. This is mainly owing to the fact that there is no standardized categorization for energy optimization potentials yet. In addition, many efficiency deficits remain undetected as a result of a non-existing efficient methodology for finding energy consumption optimization measures. The domain of information retrieval addresses this issue, as it is able to provide documents matching the user’s information demand. Nevertheless, search queries have to be sufficiently well known in order to gain adequate results. In this paper we show how ontologies can be used to support the user in defining search queries and finding optimization measures efficiently. As formal and explicit specifications of shared conceptualizations, ontologies offer the possibility to represent relevant parts of knowledge in a standardized, machine-readable manner. Therefore, ontologies improve upon data models, which are mainly used for single applications. For the purpose of energy efficiency in production environments, we provide both a methodology to build ontologies for describing energy saving measures and illustrate the application for explicit energy efficiency optimization measures.

scholarly journals METHODS FOR ENERGY EFFICIENCY AND ENERGY SAVING IN THE SMART HOME SYSTEM

2020 ◽  
Vol 1 (1) ◽  
pp. 54-59
Author(s):  
K. BOBROVNIKOVA ◽  
◽  
E. TOVSTUKHA ◽  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Smart Home ◽  
Life Support ◽  
International Energy Agency ◽  
Developed Countries ◽  
Effective Control ◽  
The European Union ◽  
Total Energy Consumption

Today, the efficient use of energy resources is one of the most important tasks. The fastest growing sector of energy consumption in the world is electricity, which is projected to grow by 56% by 2035, and in developed countries almost all the growth is due to the generation and consumption of electricity and heat. Further growth of energy consumption by the population is also expected. At the same time, almost a third of the total energy consumption is made up of certain losses, ie energy is consumed for other purposes. Against the background of global growth in energy consumption, the rate of further accumulation of CO2 emissions will increase. That is why the European Union, United Nations bodies, international financial organizations and the International Energy Agency give priority to energy efficiency issues. To this end, a set of mechanisms and practical tools for economic stimulation of measures to implement modern energy-saving technologies is used at the international level. Smart home is a system for managing the basic life support processes of both small systems (commercial, office premises, apartments, cottages) and large automated complexes (commercial and industrial complexes). One of the important tasks to be solved by the concept of a modern smart home is the problem of energy efficiency and energy saving. Effective control of heating, ventilation, air conditioning, more efficient use of traditional appliances and the introduction of energy-efficient equipment in the building are important to ensure productive, healthy and safe work and life of residents, play an important role in preventing energy loss and reduce impact on the environment. In addition, improving the efficiency of energy management is the only approach to ensuring the energy efficiency and energy saving of many existing buildings that cannot be upgraded according to the requirements of modern construction technologies. The paper presents an overview of modern methods and technologies aimed at ensuring energy efficiency and energy saving in the smart home system.

Comparison of Prognosis Methods for the Energy Consumption of Machines and Further Development with Regard to Increasing Data Availability

2016 ◽  
Vol 856 ◽  
pp. 64-72
Author(s):  
Thiemo Müller ◽  
Julian Stefan Tauschek ◽  
Johannes Glasschröder ◽  
Gunther Reinhart
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Demand ◽  
Production Systems ◽  
Data Availability ◽  
Related Data ◽  
Energy Management Systems ◽  
Shared Information ◽  
Universal Applicability ◽  
Further Development

An increasing number of companies establish energy management systems for continuous improvement in their energy efficiency and for this intensify monitoring their current energy consumption. These data can be used to gain further information about the production and to find potentials to increase its energy efficiency. In the procurement process of machinery and equipment or in the planning phase of production systems and building services, information about energy demand is rarely available, though it would be valuable for an early inclusion of energy efficiency in these processes. Therefore this paper discusses different forecast methods for energy consumption of machinery and evaluates in particular their universal applicability, effort and accuracy by analyzing them through the example of a packaging machine. In addition this paper proposes a further usage of energy-related data of machinery, which can be automatically acquired by monitoring systems for prognosticating their energy consumption as well as a possible distribution approach of this information. Therefore an own forecast method is presented, which shall process the energy-related data combined with information about dominant parameters of the product, the usage of the machine and the environmental conditions. For the distribution concept it was taken into account that the generated and shared information has to be abstracted in a way that no critical secrets of the company are revealed.

Sign in / Sign up

Export Citation Format

Share Document