Method for Increasing Energy Efficiency in Flexible Manufacturing Systems: A Case Study

Material handling in manufacturing systems is becoming easier as the automated machine technology is improved. Nowadays, most of the research aims at increasing the flexibility and improving the performance of the automatic guided vehicle (AGV). In this paper, designed and made AGV in the Industrial Control Laboratory in Royce Lab at the University of Manchester Institute of Science and Technology will be presented. For controlling the navigation of the AGV, a newly developed controller integrated fuzzy logic with programmable logic controller will be used. By using integrated fuzzy logic controller with programmable logic controller (IFLPLC), the flexibility of AGV will be increased and we achieved great advantages, which can be used in future. Since this AGV uses programmable logic controller and fuzzy logic controllers together, then it will be useful for factories which implement flexible manufacturing system (FMS). Online maintenance and sending the commands to other machines from AGV and so on are the advantages that can be used in FMS. The aim of this paper is to propose the practical example of IFLPLC. The designed AGV is able to reach the target. Further researches are required for collision avoidance and selecting the best way in FMS

Developing a hybrid programmable logic controller platform for a flexible manufacturing system

As the current situation of imperfect model algorithm of electrical equipment for energy efficiency evaluation, we set up energy efficiency DEA model. In the model, we got average load rate, average power factor and tri-phase unbalance factor as inputs indexes. And we got economic output of per unit of power consumption and energy pollution as outputs indexes. Then we transformed multiple pollutants into a pollutant index through principal component analysis. And we got it as the desired output. The result of 12 industrial enterprises in the energy efficiency of electrical equipment shows that the evaluation model is suitable for energy efficiency evaluation and system analysis. The DEA model is useful to further improvement in the energy efficiency of equipment.

The energy efficiency of space heaters is rated by Annual Fuel Utilization Efficiency (AFUE) governed by the Department of Energy in the United States which is a simple ratio of usable heat and fuel usage of a single heating device. It doesn't consider the overall performance of the heating system including not only the heating devices but also the characteristics of the building in different applications. The current AFUE method calculates only the energy efficiency which is thermodynamics first law efficiency. In this research, the systematic efficiency of a heating system rather than simple device efficiency has been defined and investigated. The systematic efficiency considers the overall efficiency of the whole heating system and it varies in the different applications even though with the same heating device. So it represents the performance of the system more precisely. Analytical models have been built to calculate both the systematic energy efficiency and exergy efficiency, and to evaluate the systematic energy and exergy efficiency of heating systems for direct fired and indirect fired heaters. Efficiency performances of the systems with these two types of heaters are compared. Sensitivities of input parameters for systematic energy efficiency are studied to show the impact towards systematic energy efficiency. Indoor carbon dioxide concentration level of direct fired heating system is also studied. In a case study, results show that systematic energy efficiency of indirect fired heating system is always constant at heater device efficiency which is 80\% while systematic energy efficiency of direct fired heating system varies from 40%-92% under different condition (heat loss coefficient, ambient temperature and air change requirement), indicating that simple device efficiency is not capable to evaluate the overall performance of heating system. New efficiency method such as systematic energy efficiency used in this research is needed to better describe the performance of the heating system. Results of indoor carbon dioxide level of direct fired heating system, from 1000 to 4500 PPM under different conditions, show that indoor air quality needs to be considered while using direct fired heating.

The European Commission outlined the energy-related products (ErPs) meant to be labelled and regulated in order to achieve the goals to reduce the European amount of CO2-emissions by 20% by 2020 compared to projections. Machine tools (MTs) fulfill all mandatory criteria to be categorized as ErP, namely: significant sales volume, significant environmental impact and significant improvement potential. However, the energy consumption and energy efficiency of MTs strongly depend on their utilization. A generic evaluation approach for quantifying a MT’s energy efficiency is still under development by the working group ISO/TC 39/WG 12, which drives forward the ISO 14955 series for environmental evaluation of MTs.This work presents an approach for a generic energy efficiency evaluation of MTs. Component-specific behavior is investigated and aggregated in order to entirely describe the power consumption of a MT for any utilization by power mapping. Power maps contain all possible operational scenarios under the condition of the component boundaries. The approach allows a generic MT evaluation independent on the utilization and forms the base for future MT energy efficiency labelling. The presented approach is applied and validated in a practical case study.

This paper presents an Axiomatic Design framework formanufacturing system design and illustrates how leancellular manufacturing can achieve volume flexibility. Axi-omatic Design creates a design framework by mappingthe functional requirements of a system to specific designparameters. Volume flexibility is often neglected as arequirement of manufacturing systems. Very few indus-tries are fortunate enough to experience stable or pre-dictable product demand. In reality, demand is oftenvolatile and uncertain. It is important that manufacturingsystem designers are aware of manufacturing systemtypes which can accommodate volume flexibility and fol-low a structured design methodology that assures that allrequirements are met by the system. INTRODUCTION Recent decades have led to the development and prolif-eration of many new paradigms in manufacturing. Withthe advent of Numerically Controlled (NC) and later Com-puter Numerically Controlled (CNC) machine tools androbotics, the complexity of manufacturing systems hasgrown considerably. In many instances, the advantagesand limitations of these new tools were not understood.This confusion led to many costly mistakes in manufac-turing system design. Many companies believed thatautomation was the wave of the future and invested inexpensive automated systems only to find that they werenot cost effective.There are two reasons why such mistakes have beenmade and continue to be made. First, the manufacturingfield as a whole does not fully understand the advantagesand disadvantages of different types of manufacturingsystems. Since the mid-1970's the variety of manufactur-ing system types has grown considerably. Since thattime, Flexible Manufacturing Systems, Agile ProductionSystems, and Lean Cellular Systems, have becomeaccepted types of manufacturing systems. Prior to that,the main types of systems were limited to Job Shops(jumbled flow systems), Disconnected Flow Lines(Batch Production), and Transfer Lines. The develop-ment of new system types complicates manufacturingsystem design considerably. Careful consideration of therequirements of the system is required to support aninformed system type selection.A major reason why highly automated manufacturing sys-tems may not be cost effective is that product demandcan be very unpredictable. Generally, the more auto-mated the system is, the less flexible it is in terms of vol-ume. An automated transfer line, for example may be themost cost effective type of system available at a particu-lar production rate. If demand increases or decreases,however, an automated system is either unable to meetthe demand or must take a variable cost increase (over-time, etc.) to do so. In many industries, demand is vola-tile and uncertain. As a result, the forecast of demand israrely accurate. Figure 1 illustrates that even with anaccurate forecast, demand will be normally distributedabout the forecast. If the forecast is skewed, the actualdistribution will be shifted either to the left or right.Figure 1. The uncertainty of the demand forecastThe problem of forecasting is magnified as the leadtimerequired to construct and validate a manufacturing sys-tem increases. As this leadtime increases, a longerrange forecast is required. The deviation ( ∆) between theforecast and the actual demand can be expected toincrease the farther into the future the forecast predicts.The second reason for ineffective manufacturing systemdesigns is that there has been no structured methodol-ogy to follow. Tools such as Quality Function Deployment(QFD) and Axiomatic Design have proven to be very

Nowadays, the energy consumption of machines is becoming increasingly important in production areas. This is mainly due to rising energy costs, but sustainability and energy savings also play an important role. This article aims to carry out a study on the energy efficiency of machine tools through the acquisition of energy data in real time. The proposed methodology is based on Patterson's definition of energy efficiency to analyse the energy consumption of the tools and evaluate its possible improvement through the development of productive, economic and environmental indicators. As a result of this study, the methodology developed is implemented in a machine tool for which the visualisation of these indicators is obtained in real time so that they can be used to help in decision-making to improve the energy efficiency of the tool. In short, this research seeks to provide a solution to one of the great challenges facing industry today due to the increase in energy costs, which is directly reflected in the cost of manufacturing.

An autonomous micro combined heat and power (Micro-CHP) is usually installed to increase energy efficiency and reduce energy costs in areas remote from large power systems. The main goal of autonomous Micro-CHP is to provide residential and industrial areas with electricity and heat. By designing an autonomous Micro-CHP, one of the key issues is the determination of rated power, since the energy efficiency of equipment and the costs of fossil fuels depend on the rated power. The mathematical model can better calculate the necessary rated power for an autonomous Micro-CHP in the case of operation with rechargeable batteries. Overall, the results have shown that the engine characteristics, operation process of three-phase synchronous generator and statistical information on loads are the criteria for improving energy efficiency.

Technologies such as Autonomous Guided Vehicles (AGVs) and the Internet of Things (IoT) increasingly disrupt traditional manufacturing and production systems. However, there is a scarcity of empirical studies synthesising and evaluating the impact of disruptive technologies on existing manufacturing systems. This study examines the impact of AGVs applying IoT on Flexible Manufacturing Systems (FMS) through a case study demonstrating the integration of AGVs with IoT in a manufacturing company. As a concept, FMS was conceived decades ago; this study uses socio-technical systems theory to elaborate the concept of FMS into the current context. Key themes uncovered from the literature review include (i) AGVs in warehouse systems, (ii) AGV scheduling and routing, (iii) Human-machine interface, and (iv) integrating and controlling AGVs/IoT. The case study demonstrates how AGVs can create smart, flexible manufacturing systems by taking the following steps: (a) problem identification, (b) performance measurement, (c) designing the proposed solution, (d) evaluate IoT systems, (e) implementation of the new solution, and (f) future improvements. The study concludes with specific recommendations to implement Industry 4.0 in manufacturing companies.

High quality and low-cost factors are among the main components of manufacturing. Nowadays, businesses need to keep up with technological innovations in order to meet these factors and survive in a competitive environment. These require the use of high-performance computer integrated manufacturing (CIM) technologies in order to manufacture products faster, inexpensively, flexibly and more efficiently. These technologies generally include computer-aided design (CAD) and computer-aided manufacturing (CAM), industrial robotics, automated material handling systems, group technology, flexible manufacturing systems (FMS), rapid prototyping (RP) operations and computer numerical controlled (CNC) machines. The main purpose of these advancements is to provide higher labour efficiency and flexibility, lower production time and a reduction of direct labour requirements. In this chapter, the effects of CIM technologies on manufacturing processes as well as product quality will be comparatively analysed. The effect of the internet of things (IoT), cyber-physical service (CPS) and cloud computing (CC) on smart manufacturing systems, which can be operated and integrated with CIM and contribute to increasing manufacturing efficiency by using information, will be revealed in detail.

The behavior mapping of systems has undergone rapid change with advances in technology. The representation has become digital with state description of the behavior. This manifestation is called Discrete Event Systems (DES), exhibiting properties such as non – determinism, conflict and parallelism[1]-[3]. Supervisory Control Theory (SCT)[8],[9] is chosen as a modeling paradigm and Programmable Logic Controllers (PLC) [10] – [12] as an implementation tool for DES. This work investigates the use of Fuzzy Petri nets in supervisory control and suggests a modified and improved version called Fuzzy Automation Petri net (FAPN) as a modeling tool. It presents a systematic approach to the synthesis of Fuzzy Petri net based supervisor for the forbidden state problem using supervisory design procedure. The controlled model of the system can be constructed from this FAPN net structure. The implementation is using Flexible Manufacturing System (FMS) as an example of DES. The results can be interpreted and applied to high level manufacturing systems, where the role of the supervisor is to coordinate the control of multiple machines or to low level manufacturing systems, where the control function is to switch ON/OFF with respect to the dynamics between different valves.

In order to develop, test, and validate system control software for managing flexible manufacturing systems, most laboratories have constructed an experimental testbed using actual manufacturing equipment. These experimental systems typically occupy a large amount of lab space, cost hundreds of thousands of dollars to construct, and require considerable human expertise to operate. In addition, given their experimental nature, there is little or no opportunity to recapture the costs through the manufacturing of commercial products. We propose an alternative solution for providing the essential testbed. Using dedicated micro-controllers (programmable logic controllers), we have developed a physical emulator for a flexible manufacturing cell which faithfully replicates the operating characteristics of an ensemble of physical equipment that would typically comprise a flexible manufacturing system. The proposed system has several unique advantages over the traditional testbeds. First, it is inexpensive and can easily be replicated at other laboratories. Second, it can be easily reconfigured to consider alternative manufacturing scenarios. Third, it can consider an emulated environment that is far more complex than those that are typically addressed by testbeds using actual equipment. Finally, it is totally reliable and safe, and it requires minimal expertise to operate. The paper discusses the design and operational characteristics of the developed emulator along with its anticipated uses and current limitations.

Problem Statement. Energy efficiency of the housing stock is one of the most important components of sustainable development in Ukraine, especially in the context of rising energy resource tariffs and global environmental challenges. State policy in this area aims to reduce energy costs, improve housing quality, and enhance citizens’ living conditions. The relevance of the topic is determined by the need to develop comprehensive measures that ensure the effective use of energy resources, adapt buildings to new technologies, and implement innovative solutions. The main directions for improving state policy include the formation of investment programs for the modernization of the housing stock, the introduction of a financing system for energy-efficient projects through state and local budgets, as well as the involvement of international financial institutions. Additionally, it is important to ensure informational and educational campaigns for the population regarding the benefits of energy efficiency, as well as to develop mechanisms to encourage businesses and citizens to implement energy-efficient technologies. The introduction of new construction standards that take into account environmental and energy-efficient norms will become a guarantee of sustainable development for the housing stock. The purpose of this article is to analyze existing problems in the field of energy efficiency of the housing stock in Ukraine and propose measures that can enhance the effectiveness of state policy in this area. Conclusion. State policy in the field of energy efficiency of the housing stock is a key factor influencing the stability and development of the energy sector in Ukraine. The development and implementation of comprehensive measures aimed at increasing energy efficiency, supporting investments, and promoting ecological norms will create conditions for reducing energy costs for the population and improving housing quality. Improving financing mechanisms and cooperating with international organizations will ensure the sustainable development of the construction sector and adapt the housing stock to modern energy efficiency requirements.

Self-Organising Electronic Institutions and Flexible Manufacturing Systems

Methods of determining the energy efficiency of machine tools are analyzed, including methods based on the input energy balance, the expenditures in machining, and energy losses in the shaping structure of the machine tool. The energy efficiency may be assessed in terms of the energy ratio of the physical processes within the machine tool. On that basis, metal-cutting machines may be classified by energy efficiency.