Configuration Of Production System Research Articles

Research on Capacity Optimization Configuration of Renewable Energy Off Grid Hydrogen Production System Considering Collaborative Electrolysis

This study proposes a multitype electrolytic collaborative hydrogen production model for optimizing the capacity configuration of renewable energy off grid hydrogen production systems. The electrolytic hydrogen production process utilizes the synergistic electrolysis of an alkaline electrolyzer (AEL) and proton exchange membrane electrolyzer (PEMEL), fully leveraging the advantages of the low cost of the AEL and strong regulation characteristics of the PEMEL. For the convenience of the optimization solution, the article constructs a mixed linear optimization model that considers the constraints during system operation, with the objective function of minimizing total costs while meeting industrial production requirements. Gurobi is used for the optimal solution to obtain the optimal configuration of a renewable energy off grid hydrogen production system. By comparing and analyzing the optimal configuration under conventional load and high-load conditions, it is concluded that collaborative electrolysis has advantages in improving resource consumption and reducing hydrogen production costs. This is of great significance for optimizing the capacity configuration of off grid hydrogen production systems and improving the overall economic benefits of the system.

European Green Deal: Justification of the Relationships between the Functional Indicators of Bioenergy Production Systems Using Organic Residential Waste Based on the Analysis of the State of Theory and Practice

Based on the analysis conducted on the state of theory and practice, the expediency of assessing the relationships between the functional indicators of bioenergy production systems using the organic waste of residential areas is substantiated in the projects of the European Green Deal. It is based on the use of existing results published in scientific works, as well as on the use of methods of system analysis and mathematical modeling. The proposed approach avoids limitations associated with the one-sidedness of sources or subjectivity of data and also ensures complete consideration of various factors affecting the functional indicators of the bioenergy production system from the organic waste of residential areas. Four types of organic waste generated within the territory of residential areas are considered. In our work, we used passive experimental methods to collect data on the functional characteristics of bioenergy production systems, mathematical statistics methods to process and interpret trends in the functional characteristics of bioenergy production systems using municipal organic waste, and mathematical modeling methods to develop mathematical models that reflect the patterns of change in the functional characteristics of bioenergy production systems. The results indicate the presence of dependencies with close correlations. The resulting dependencies can be used to optimize processes and increase the efficiency of bioenergy production. It was found that: (1) yard waste has the highest volume of the total volume of solid organic substances but has a low yield of biogas and low share of methane production; (2) food waste has the highest yield of biogas and, accordingly, the highest share of methane production; (3) mixed organic waste has the lowest volume of the total volume of solid organic substances and the lowest content of volatile organic substances. The amount of electricity and thermal energy production varies by type of organic waste, with mixed organic waste having a higher average amount of electricity production compared to other types of waste. It was established that the production volume of the solid fraction (biofertilizer) is also different for different types of organic waste. Less solid fraction is produced from food waste than from yard waste. The obtained research results are of practical importance for the development of sustainable bioenergy production from organic waste in residential areas during the implementation of the European Green Deal projects. They provide further research on the development of effective models for determining the rational configuration of bioenergy production systems using organic waste for given characteristics of residential areas.

Analysis of metaheuristic optimisation techniques for simulated matrix production systems

Increasing demand for individualised products has led to the concept of mass customisation, combining high product variety with production efficiency coming along with mass production. Companies are moving to matrix production systems with complex product flows for mass customisation. One challenge in such systems is the determination of optimal system configurations to fulfil future demands while minimising production costs. An approach to determine the ideal configuration is to use metaheuristics like genetic algorithms or simulated annealing to optimise simulation models. However, it is unclear which methods are ideally suited to finding the best solutions. This contribution compares the performance of genetic algorithms and simulated annealing when optimising the configuration of a company-specific matrix production system using discrete event simulation. The methods are evaluated using different objective functions. For the genetic algorithm, different observation strategies are also tested. Overall, the simulated annealing approach delivers better results with shorter solution times. The contributing factors leading to the different results are discussed, and areas for future research are pointed out.

A Cost/Benefit and Flexibility Evaluation Framework for Additive Technologies in Strategic Factory Planning

There is a growing demand for more flexibility in manufacturing to counter the volatility and unpredictability of the markets and provide more individualization for customers. However, the design and implementation of flexibility within manufacturing systems are costly and only economically viable if applicable to actual demand fluctuations. To this end, companies are considering additive manufacturing (AM) to make production more flexible. This paper develops a conceptual model for the impact quantification of AM on volume and mix flexibility within production systems in the early stages of the factory-planning process. Together with the model, an application guideline is presented to help planners with the flexibility quantification and the factory design process. Following the development of the model and guideline, a case study is presented to indicate the potential impact additive technologies can have on manufacturing flexibility Within the case study, various scenarios with different production system configurations and production programs are analyzed, and the impact of the additive technologies on volume and mix flexibility is calculated. This work will allow factory planners to determine the potential impacts of AM on manufacturing flexibility in an early planning stage and design their production systems accordingly.

Type-2 fuzzy-logic based control of photovoltaic-hydrogen production systems

Green hydrogen will play an important role for sustainable development, it can be considered as a promising solution for energy transition. In this paper, direct and indirect-coupled configuration of hydrogen production system consisted of Photovoltaic (PV) source and electrolyzer stack are investigated. A study on power loss and efficiency in PV-electrolyzer system is conducted for both cases. Optimal matching conditions in directly coupled hydrogen system can be achieved by modifying the configuration of series/parallel cells in electrolyzer stack or PV generator. However, the energy transfer can be improved by incorporating a buck converter between PV string and electrolyzer stack. In this article, the type-2 fuzzy inference system is proposed to control the operating point of PV string by adjusting the duty cycle of control signal of buck converter. A comparison with classical MPPT methods is carried out in order to verify the efficiency of suggested technique. It has been found that the indirect-coupled hydrogen system can achieve higher energy transfer rate by ensuring continuous extracting of maximum power of PV source under various operating conditions. The obtained results, under Matlab/Simulink environment, demonstrated a satisfactory performance of type-2 fuzzy logic controller in both transient and permanent regimes. We obtain a minimal power loss value (less than 8.1%) in directly-coupled hydrogen production system, in addition a satisfactory value of efficiency (more than 93%) has been obtained.

Multi-objective optimization configuration of wind-solar coupling hydrogen production system

The existing research on the wind solar coupling hydrogen generation system lacks the evaluation of factors such as the reliability of power supply to the microgrid system. This paper establishes a multi-objective optimization configuration model of wind-solar coupling hydrogen generation system under grid-connected operation mode for hydrogen generation. From the perspective of system economy and stability analysis, the model optimizes the capacity of the wind power unit, photovoltaic unit, energy storage unit, and hydrogen generation unit to improve the economy and reliability of microgrid operation, to minimize load loss rate, system annual cost, renewable energy power generation loss rate, and energy surplus rate.

Optimal Configuration of Coupled Optical Storage Hydrogen Production System Considering Multi-body and Multi-objective Joint Optimization

With the development of siting and capacity setting methods for coupled optical-storage hydrogen production systems, difficulties such as the complexity of constraints in multi-body and multi-objective system planning models, the decline of electrolytic tank life, and non-linear and non-time-series have emerged one after another. To address these difficulties, this paper proposes a double-layer planning capacity configuration method for coupled optical-storage-grid hydrogen production for transmission and transformer systems, which solves the explicit and implicit coupled double-layer optimization problems under the mixed-integer optimization framework with traditional cone optimization techniques combined with swarm intelligent optimization techniques to achieve joint optimal planning configuration for coupled optical-storage-hydrogen production systems.

Optimising renewable generation configurations of off-grid green ammonia production systems considering Haber-Bosch flexibility

Green ammonia has received increasing interest for its potential as an energy carrier in the international trade of renewable power. This paper considers the factors that contribute to producing cost-competitive green ammonia from an exporter’s perspective. These factors include renewable resource quality across potential sites, operating modes for off-grid plants, and seasonal complementarity with trade buyers. The study applies a mixed-integer programming model and uses Australia as a case study because of its excellent solar and wind resources, and the potential for synergy between Southern Hemisphere supply and Northern Hemisphere demand. Although renewable resources are unevenly distributed across Australia and present distinct diurnal and seasonal variability, modelling shows that most of the pre-identified hydrogen hubs in each state and territory of Australia can produce cost-competitive green ammonia providing the electrolysis and Haber-Bosch processes are partially flexible to cope with the variability of renewables. Flexible operation reduces energy curtailment and leads to lower storage capacity requirements using batteries or hydrogen storage, which would otherwise increase system costs. In addition, an optimised combination of wind and solar can reduce the magnitude of storage required. Providing that a partially flexible Haber Bosch plant is commercially available, the modelling shows a levelised cost of ammonia (LCOA) of AU$756/tonne and AU$659/tonne in 2025 and 2030, respectively. Based on these results, green ammonia would be cost-competitive with grey ammonia in 2030, given a feedstock natural gas price higher than AU$14/MBtu. For green ammonia to be cost-competitive with grey ammonia, assuming a lower gas price of AU$6/MBtu, a carbon price would need to be in place of at least AU$123/tonne. Given that there is a greater demand for energy in winter concurrent with lower solar power production, there may be opportunities for solar-based Southern Hemisphere suppliers to supply the major industrial regions, most of which are located in the Northern Hemisphere.

Development of a system for building a cloud-based digital twin as an informational assistance system for context-based dynamic configuration of cyber-physical hybrid production systems

Development of a system for building a cloud-based digital twin as an informational assistance system for context-based dynamic configuration of cyber-physical hybrid production systems

A Matheuristic based on Ant Colony System for the Combined Flexible Jobshop Scheduling and Vehicle Routing Problem*

Nowadays, market behavior and globalization mean that end consumers are waiting very quickly for their orders to be delivered. This context forces companies to have high availability of finished products. For this reason, the industries that make up the supply chains are obliged to implement strategies to meet this customer need. One efficient practice is the integration of production and transportation activities. In the literature, few research works integrate the scheduling of production tasks with the vehicle routing. This paper aims at proposing a solution approach for the combined problem. The production system configuration is defined as a flexible jobshop, while the distribution problem is modeled as a vehicle routing problem. The proposed approach consists of two parts. First, production makespan is minimized through a hybrid algorithm based on ant colony system and local search. Then, the routing problem is solved optimally using mathematical programming in order to minimize the total travel time. Benchmark instances from the literature are adapted to deal with the combined problem. Experimental results show the efficiency and effectiveness of the proposed algorithm.

Improving the efficiency of customized production for personalized engineering products at defense industry enterprises based on its configuration management

The configuration managing technology of products configuration and the production system in order to increase the efficiency of designing and manufacturing personalized engineering products is considered. A semantic model of conjugation of the product configuration and production system configuration, formed on the grounds of defense industry enterprises (DIE), is proposed. An analysis orders algorithm for the manufacture of civilian products at DIE at the stage of preparing tender documentation is developed. Keywords defense industry enterprise, configuration management, civilian and dual-use products, import substitution

Novel heuristic approach to integrating task sequencing and production system configuration

The robot system integration (SI) business targets the construction of production lines for various products that differ from customer to customer. Improving the efficiency of line design is important for increasing profits in the SI business. Especially in the construction of assembly lines, the optimal system configuration, with an appropriate combination of robotic and human stations, is critical for maximizing the return on investment of customers. Yet, the optimal system configuration depends heavily on the task sequence in the process plan. In this paper, task sequencing and system configuration are regarded as two interdependent sub-problems of line design. The exact joint optimum of the two problems can be found only if they are solved together, in an integrated way. However, this is computationally intractable for problems of industrially relevant sizes. To overcome this challenge, a heuristic method exploiting industrial knowledge is proposed for solving the two problems simultaneously. The heuristic constructs promising task sequences according to the capabilities of the applicable resources, considering aspects such as, among others, human work quality or robot tool change times. Then, a close-to-optimal system configuration is computed by considering the promising task sequences and their various relevant combinations. The proposed method is illustrated in a case study on the assembly of electrical components in the automotive industry.

The Moon Project: Where Management Meets Mathematics

This article studies a cost project problem identified here as the Moon project with mathematical laws. The Moon project is a program cost project regulated by certain constraints with principal variable N∈Z that survives on project h∈H only if it survives the lowest level (level 1). For this particular problem, we model the total cost T for mounting a Moon project under project coordinates involving the inward payables (w), the outward payables (x), consumables (y), cross subsidisation (z) as independent coordinates and sufficient for describing the configuration of complicated production systems. Additionally, optimal path analysis to completeness in form of examples and remarks on Moon projects survival chances is provided.

A novel data-driven approach to support decision-making during production scale-up of assembly systems

In today's manufacturing settings, a sudden increase in the customer demand may enforce manufacturers to alter their manufacturing systems either by adding new resources or changing the layout within a restricted time frame. Without an appropriate strategy to handle this transition to higher volume, manufacturers risk losing their market competitiveness. The subjective experience-based ad-hoc procedures existing in the industrial domain are insufficient to support the transition to a higher volume, thereby necessitating a new approach where the scale-up can be realised in a timely, systematic manner. This research study aims to fulfill this gap by proposing a novel Data-Driven Scale-up Model, known as DDSM, that builds upon kinematic and Discrete-Event Simulation (DES) models. These models are further enhanced by historical production data and knowledge representation techniques. The DDSM approach identifies the near-optimal production system configurations that meet the new customer demand using an iterative design process across two distinct levels, namely the workstation and system levels. At the workstation level, a set of potential workstation configurations are identified by utilising the knowledge mapping between product, process, resource and resource attribute domains. Workstation design data of selected configurations are streamlined into a common data model that is accessed at the system level where DES software and a multi-objective Genetic Algorithm (GA) are used to support decision-making activities by identifying potential system configurations that provide optimum scale-up Key Performance Indicators (KPIs). For the optimisation study, two conflicting objectives: scale-up cost and production throughput are considered. The approach is employed in a battery module assembly pilot line that requires structural modifications to meet the surge in the demand of electric vehicle powertrains. The pilot line is located at the Warwick Manufacturing Group, University of Warwick, where the production data is captured to initiate and validate the workstation models. Conclusively, it is ascertained by experts that the approach is found useful to support the selection of suitable system configuration and design with significant savings in time, cost and effort.

Ergodynamic cooperative as a driving force for solving the employment problem

The form of association of producers existed at the level of primitive production, but it quickly collapsed under the influence of the labor division. If we create such a form in modern conditions, in addition to taking into account the large role of complex automation of all types of production activities, the existing factors of ergodynamics should also be taken into consideration. The article examines a new approach to the problem of employment based on the adoption of the paradigm of a radical change in the configuration of the production system. It is demonstrated that in the case when the production system consists of a number of producers, among which the connections are broken, the workers released as a result of automation naturally and inevitably pass into the category of unemployed. Trying to organize a new production of new products, manufacturers face a cyclical pattern, increasing the number of unemployed. While maintaining the image of traditional production based on the production system, managers try to find extravagant methods to solve the issue of employment, although, in fact, it is not the problem of employment that is being tackled, but the issue of social support for the unemployed. An analysis of existing trends in production is necessary not only to develop objective measures to enhance efficiency. A comprehensive analysis of trends, combined with the introduction of new approaches to the description of labor activity, allowed revealing and justifying a new look at the strategy for improving production. This makes it possible to describe a new type of production systems, namely self-developing production systems, at the conceptual level. The presence in the description of such production of a model of real transformation of labor activity allows creating a system with an internal structure of self-development. Such self-developing production systems do not need external influences and are invariant in a wide variety of social environments. The article can be useful for both economists and production managers.

Simulated-based methodology for the interface configuration of cyber-physical production systems

Besides managing accruing data in production systems, Digital Twins provide additional services like the simulation or control of production systems. The Digital Twin and its real-world physical counterpart need to be interconnected using sensors and actuators to enable such services. This article proposes a simulation-based method to design and evaluate such an interface. Applying concepts from the area of software-in-the-loop, it proposes the use of a so-called Physical Twin: a simulation model which mimics the abilities of the physical system but allows simulation-based experiments to optimise the interface. After presenting the general approach, the article provides an application example of the proposed procedure. A Digital and a Physical Twin are implemented for an application scenario and connected using a simple TCP/IP interface. By varying the number of sensors as well as considering component breakdowns in the Physical Twin, this setup allows evaluating different configurations in terms of production performance. The evaluation confirms that configurations with more sensors result in higher production performance of the system. However, a saturation of the performance gain is also observable when exceeding a certain number of sensors. Therefore, determining the optimal configuration is vital to optimise the interface from a financial point of view.

Hydronic configurations of hybrid heat production systems in buildings: General design methodology and case studies

Hybrid heat production systems, in which sustainable technologies such as Combined Heat and Power (CHP) or heat pumps are combined with auxiliary heaters, have the potential to increase energy efficiency in buildings. In order to exploit this potential, a proper hydronic configuration of the production system is of uttermost importance. Unfortunately, both scientific literature and design guides have focussed little on this aspect.Therefore, this paper proposes a general simulation-based design methodology for selecting the hydronic configuration of a hybrid production system. To illustrate the methodology, it is applied on different case studies in which either a CHP or an Electrical ground-coupled Heat Pump (EHP) is assisted by an auxiliary boiler. The considered apartment building is equipped with a collective heating system for both space heating and domestic hot water (DHW) production, and four different combinations of the temperature levels are considered.Results show that if a CHP is considered, the auxiliary boiler should be implemented in parallel and be assisted by a modulating valve: this increases the Relative Primary Energy Savings (RPES) with up to 6.2 percentage points. EHPs require a separate circuit in the production system for space heating and DHW, preferably with preheating of the domestic cold water (an increase in RPES of up to 16.1 percentage points was reported).The use of a new type of Load Duration Curve to analyse the simulation results proved to be a comprehensible measure for decision making at the level of every stakeholder in the design process. In conclusion, the proposed methodology can assist these stakeholders in their pursuit of high performance hybrid heat production systems.

A simulation-based approach for time allowances assessment during production system design with consideration of worker’s fatigue, learning and reliability

Health and safety of human operators in production systems is tightly linked to overall work system design. Well-designed production systems must grant adequate allowances to operators, to cope with the variability of predictable situations, whether normal or not. In this article, time allowances concept is presented from two standpoints: industrial engineering and occupational risk prevention field. This is followed by an introduction of a new time allowances indicator. Combined with an agent-based simulation model, this indicator can be used to assess time allowances in a given work organization during its design process. The proposed model integrates worker’s fatigue, learning and reliability as relevant human factors. To uphold the article proposal, three production system configurations are investigated: a classical production line designed based on Ford work paradigm, a cellular configuration with autonomous breaks, inspired from Volvo Uddevalla plant and finally, a hybrid configuration, cellular with planned breaks. The simulations showed that cellular configuration with autonomous breaks grants to operators the time allowances they need to carry out their work activity safely and efficiently.

Methodical approach for the development of a platform for the configuration and operation of turnkey production systems

Shorter product lifecycles lead not only to faster time-to-market for products but also to the need for just as fast available associated production systems. These shorter product lifecycles, as well as the increasing individualization of products, also result in further decreasing production lot sizes. Young companies in China in particular are characterized by a very high speed of innovation but may not have the necessary manufacturing knowledge or capacities to bring their developed products to the market with a scalable production. For this reason, there is a great need to quickly set up and commission turnkey production systems or to reconfigure existing production systems for new production tasks in the shortest possible time. This paper describes the design and architecture of a cloud platform with the aim to support a manufacturer independent design process for turnkey production systems. This process ranges from the product to be manufactured to the operation of the production system. Firstly, the structure and methodology used to link the various objectives are discussed. The system for recording and structuring product and production system data to create reusable modules from components and machines is described. Subsequently, the use of standardized modules is developed to support reconfiguration of the production system during operation. In addition, the digital business models tailored to the production system are proposed to the platform user for commissioning and operation of the plant. A case study is conducted to validate the proposed methodology.

Concept for the Configuration of Turnkey Production Systems

Shorter product lifecycles and increasing individualization of products lead to the necessity for a reoccurring process, which includes the selection and configuration of production systems to provide a system that produces the product. Especially in fast developing countries like China, the offer for this knowledge can hardly supply the demand. In order to solve this, this paper presents a systematic approach in the form of a multi-stage process. In the first stage, a configuration logic maps product requirements with the properties and specifications of production machines together with equipment and matches them using a uniform data information model for both products and production modules. In the second stage, the turnkey production system is set up, commissioned and operated based on the Industrie 4.0 administration shell. The presented approach has been prototypically implemented on an online platform and demonstrated on a real production system using a new product that has been integrated into production.