Математическое моделирование процессов выполнения пакетов заданий в конвейерных системах с промежуточными буферами ограниченных размеров

Modern methods of process planning in conveyor systems with buffers of a certain size between processing devices allow optimizing schedules for single tasks or fixed task packages with a limited number of them and a limited number of devices. The use of mathematical models of the processes of performing single tasks (task packages) used by these methods in optimizing the composition of packages and schedules for their execution in systems with an arbitrary number of packages and devices is impossible. At the same time, mathematical models of the processes of executing task packages in conveyor systems in the presence of buffers of limited sizes between devices are the basis for the development of methods for optimizing their (package) compositions and schedules for the implementation of actions with them on the devices of conveyor systems. In this regard, the article develops mathematical models of multi-stage processes of performing an arbitrary number of task packages in conveyor systems in the presence of intermediate buffers of limited sizes for two and three devices, as well as for an arbitrary number of devices. The use of these models makes it possible to determine the time points of the start of the execution of task packages on the devices of conveyor systems, taking into account the limited size of intermediate buffers, as well as the duration of time intervals for the use of these resources and the efficiency of their use over time. An algorithm has also been developed for mathematical modeling of the processes of executing task packages in conveyor systems in the presence of intermediate buffers of limited size, which calculates the time characteristics of these processes based on a given order of implementation of actions with task packages on the devices of conveyor systems. An application has been developed that implements synthesized mathematical models of the processes of executing task packages in conveyor systems with intermediate buffers of limited sizes and an appropriate method for modeling these processes. Versatile testing of the developed application has shown that the obtained mathematical models and the modeling method adequately describe the course of multi-stage processes of task packages in pipeline systems, set using different values of their (processes) parameters.Современные методы планирования процессов в конвейерных системах с буферами определенного размера между обрабатывающими приборами позволяют оптимизировать расписания выполнения единичных заданий либо фиксированных пакетов заданий при их ограниченном количестве и ограниченном количестве приборов. Применение математических моделей процессов выполнения единичных заданий (пакетов заданий), используемых этими методами, при оптимизации составов пакетов и расписаний их выполнения в системах с произвольным количеством пакетов и приборов является невозможным. В то же время математические модели процессов выполнения пакетов заданий в конвейерных системах при наличии буферов ограниченных размеров между приборами являются основой для разработки методов оптимизации их (пакетов) составов и расписаний реализации действий с ними на приборах конвейерных систем. В связи с этим в статье разработаны математические модели многостадийных процессов выполнения произвольного количества пакетов заданий в конвейерных системах при наличии промежуточных буферов ограниченных размеров для двух и трех приборов, а также для произвольного количества приборов. Использование этих моделей позволяет определять моменты времени начала выполнения пакетов заданий на приборах конвейерных систем с учетом ограниченных размеров промежуточных буферов, а также длительности интервалов времени использования этих ресурсов и эффективность их использования в течение времени. Также разработан алгоритм математического моделирования процессов выполнения пакетов заданий в конвейерных системах при наличии промежуточных буферов ограниченных размеров, осуществляющий на основе заданного порядка реализации действий с пакетами заданий на приборах конвейерных систем вычисление временных характеристик этих процессов. Осуществлена разработка приложения, реализующего синтезированные математические модели процессов выполнения пакетов заданий в конвейерных системах с промежуточными буферами ограниченных размеров и соответствующий метод моделирования этих процессов. Разностороннее тестирование разработанного приложения показало, что полученные математические модели и метод моделирования адекватно описывают ход многостадийных процессов выполнения пакетов заданий в конвейерных системах, задаваемый с использованием различных значений их (процессов) параметров

A Linear Programming Model for Renewable Energy Aware Discrete Production Planning and Control

Industrial production in the EU, like other sectors of the economy, is obliged to stop producing greenhouse gas emissions by 2050. With its Green Deal, the European Union has already set the corresponding framework in 2019. To achieve Net Zero in the remaining time, while not endangering one's own competitiveness on a globalized market, a transformation of industrial value creation has to be started already today. In terms of energy supply, this means a comprehensive electrification of processes and a switch to fully renewable power generation. However, due to a growing share of renewable energy sources, increasing volatility can be observed in the European electricity market already. For companies, there are mainly two ways to deal with the accompanying increase in average electricity prices. The first is to reduce consumption by increasing efficiency, which naturally has its physical limits. Secondly, an increasing volatile electricity price makes it possible to take advantage of periods of relatively low prices. To do this, companies must identify their energy-intensive processes and design them in such a way as to enable these activities to be shifted in time. This article explains the necessary differentiation between labor-intensive and energy intensive processes. A general mathematical model for the holistic optimization of discrete industrial production is presented. With the help of this MILP model, it is simulated that a flexibilization of energy intensive processes with volatile energy prices can help to reduce costs and thus secure competitiveness while getting it in line with European climate goals. On the basis of real electricity market data, different production scenarios are compared, and it is investigated under which conditions the flexibilization of specific processes is worthwhile

A novel Tiki-Taka algorithm to optimize hybrid flow shop scheduling with energy consumption

Hybrid flow shop scheduling (HFS) has been thoroughly studied due to its significant impact on productivity. Besides the impact on productivity, the abovementioned problem has attracted researchers from different background because of its difficulty in obtaining the most optimum solution. HFS complexity provides good opportunity for researcher to propose an efficient optimization method for the said problem. Recently, research in HFS has moved towards sustainability by considering energy utilization in the study. Consequently, the problem becomes more difficult to be solved via existing approach. This paper modeled and optimized HFS with energy consumption using Tiki-Taka Algorithm (TTA). TTA is a novel algorithm inspired by football playing style that focuses on short passing and player positioning. In different with existing metaheuristics, the TTA collected information from nearby solution and utilized multiple leaders’ concept in the algorithm. The research began with problem modeling, followed by TTA algorithm formulation. A computational experiment is then conducted using benchmark problems. Then, a case study problem is presented to assess the applicability of model and algorithm in real-life problems. The results indicated that the TTA consistently was in the first and second ranks in all benchmark problems. In addition, the case study results confirmed that TTA is able to search the best fitness solution by compromising the makespan and total energy utilization in the production schedule. In future, the potential of TTA will be further investigated for flexible hybrid flow shop scheduling problems

Hybrid flow shop scheduling problem with energy utilization using non-dominated sorting genetic algorithm-III (NSGA-III) optimization

Hybrid flow shop scheduling (HFS) is an on sought problem modelling for production manufacturing. Due to its impact on productivity, researchers from different backgrounds have been attracted to solve its optimum solution. The HFS is a complex dilemma and provides ample solutions, thus inviting researchers to propose niche optimization methods for the problem. Recently, researchers have moved on to multi-objective solutions. In real-world situations, HFS is known for multi-objective problems, and consequently, the need for optimum solutions in multi-objective HFS is a necessity. Regarding sustainability topic, energy utilization is mainly considered as one of the objectives, including the common makespan criteria. This paper presents the existing multi-objective approach for solving energy utilization and makespan problems in HFS scheduling using Non-Dominated Sorting Genetic Algorithm-III (NSGA-III), and a comparison to other optimization models was subjected for analysis. The model was compared with the most sought algorithm and latest multi-objective algorithms, Strength Pareto Evolutionary Algorithm 2 (SPEA -II), Multi-Objective Algorithm Particle Swarm Optimization (MOPSO), Pareto Envelope-based Selection Algorithm II (PESA-II) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). The research interest starts with problem modelling, followed by a computational experiment with an existing multi-objective approach conducted using twelve HFS benchmark problems. Then, a case study problem is presented to assess all models. The numerical results showed that the NSGA-III obtained 50% best overall for distribution performance metrics and 42% best in convergence performance metrics for HFS benchmark problems. In addition, the case study results show that NSGA-III obtained the best overall convergence and distribution performance metrics. The results show that NSGA-III can search for the best fitness solution without compromising makespan and total energy utilization. In the future, these multi-objective algorithms’ potential can be further investigated for hybrid flow shop scheduling problems

Material and energy flows of the iron and steel industry: status quo, challenges and perspectives

Integrated analysis and optimization of material and energy flows in the iron and steel industry have drawn considerable interest from steelmakers, energy engineers, policymakers, financial firms, and academic researchers. Numerous publications in this area have identified their great potential to bring significant benefits and innovation. Although much technical work has been done to analyze and optimize material and energy flows, there is a lack of overview of material and energy flows of the iron and steel industry. To fill this gap, this work first provides an overview of different steel production routes. Next, the modelling, scheduling and interrelation regarding material and energy flows in the iron and steel industry are presented by thoroughly reviewing the existing literature. This study selects eighty publications on the material and energy flows of steelworks, from which a map of the potential of integrating material and energy flows for iron and steel sites is constructed. The paper discusses the challenges to be overcome and the future directions of material and energy flow research in the iron and steel industry, including the fundamental understandings of flow mechanisms, the dynamic material and energy flow scheduling and optimization, the synergy between material and energy flows, flexible production processes and flexible energy systems, smart steel manufacturing and smart energy systems, and revolutionary steelmaking routes and technologies

Energy Efficient Policies, Scheduling, and Design for Sustainable Manufacturing Systems

Climate mitigation, more stringent regulations, rising energy costs, and sustainable manufacturing are pushing researchers to focus on energy efficiency, energy flexibility, and implementation of renewable energy sources in manufacturing systems. This thesis aims to analyze the main works proposed regarding these hot topics, and to fill the gaps in the literature. First, a detailed literature review is proposed. Works regarding energy efficiency in different manufacturing levels, in the assembly line, energy saving policies, and the implementation of renewable energy sources are analyzed. Then, trying to fill the gaps in the literature, different topics are analyzed more in depth. In the single machine context, a mathematical model aiming to align the manufacturing power required to a renewable energy supply in order to obtain the maximum profit is developed. The model is applied to a single work center powered by the electric grid and by a photovoltaic system; afterwards, energy storage is also added to the power system. Analyzing the job shop context, switch off policies implementing workload approach and scheduling considering variable speed of the machines and power constraints are proposed. The direct and indirect workloads of the machines are considered to support the switch on/off decisions. A simulation model is developed to test the proposed policies compared to others presented in the literature. Regarding the job shop scheduling, a fixed and variable power constraints are considered, assuming the minimization of the makespan as the objective function. Studying the factory level, a mathematical model to design a flow line considering the possibility of using switch-off policies is developed. The design model for production lines includes a targeted imbalance among the workstations to allow for defined idle time. Finally, the main findings, results, and the future directions and challenges are presented

Energy aware hybrid flow shop scheduling

Only if humanity acts quickly and resolutely can we limit global warming' conclude more than 25,000 academics with the statement of SCIENTISTS FOR FUTURE. The concern about global warming and the extinction of species has steadily increased in recent years

Digitization of the work environment for sustainable production

Global pandemics, devastating wars and natural disasters with increasing frequency and impact are disrupting previously carefully balanced manufacturing networks. All industrial companies are required to examine their operations and adjust accordingly. The increasing cost of resources require enterprises to re-design their value creation processes to be more sustainable, to optimize the supplier network to become more resilient and to accelerate digitizing of operations to enhance operational effectiveness. This year's WGAB research seminar is themed around Digitization of the work environment for sustainable production and seeks to contribute solutions to the current challenges. The scientific discourse aims to advance the sustainable and data-based organization of value creation processes. Exemplary efforts for the sustainable production of 3D printed footwear and the circular supply chain of energy production will be discussed. With advances in sensory data collection in cyber-physical production systems (CPPS), there are new opportunities for sensing the status of manufacturing systems, which enable advanced data analytics to contribute to a sustainable production. Intelligent processes enable sustainable value creation and bi-directional knowledge exchange between humans and machines. With people at the centre of the CPPS, production systems shall be both adaptive and personalized for every worker. People need to be involved in the technological and organizational changes. Simulating the migration from a linear economy to a circular economy supports the trend of regionalized production networks. Digital assistance systems are tested to back up resilient manufacturing. We would like to thank all authors for their efforts in preparing the contributions, which are valuable inputs to the discourse to solve the current challenges