The way humans work in production and logistics systems is changing. The evolution of technologies, Industry 4.0 applications, and societal changes, such as ageing workforces, are transforming ...operations processes. This transformation is still a “black-box” for many companies, and there are calls for new management approaches that can help to successfully overcome the future challenges in production and logistics.
While Industry 4.0 emerges, companies have started to use advanced control tools enabled by real-time monitoring systems that allow the development of more accurate planning models that enable proactive managerial decision-making. Although we observe an increasing trend in automating human work in almost every industry, human workers are still playing a central role in many production and logistics systems. Many of these planning models developed for managerial decision support, however, do not consider human factors and their impact on system or employee performance, leading to inaccurate planning results and decisions, underperforming systems, and increased health hazards for employees.
This paper summarizes the vision, challenges and opportunities in this research field, based on the experience of the authors, members of the Working Group 7 (WG7) “Human factors and ergonomics in industrial and logistic system design and management” of the IFAC Technical Committee (TC) 5.2 “Manufacturing Modelling for Management and Control". We also discuss the development of this research stream in light of the contributions presented in invited sessions at related IFAC conferences over the last five years. The TC 5.2 framework is adapted to include a human-centered perspective. Based on this discussion, a research agenda is developed that highlights the potential benefits and future requirements for academia and society in this emerging research field. Promising directions for future research on human factors in production and logistics systems include the consideration of diversity of human workers and an in-depth integration of Industry 4.0 technologies in operations processes to support the development of smart, sustainable, human-centered systems.
Ochratoxins (OTs) are a group of mycotoxins produced by Aspergillus and Penicillium spp. which are ubiquitous. They infect the crops during pre- and post-harvest conditions and contaminate various ...food and feed. Among all the OTs produced, ochratoxin A (OTA) poses serious health issues like neurotoxicity and carcinogenesis. The harmful impact of the toxins is observed in both humans and animals. The toxins get accumulated in the organs of animals through the contaminated animal-feed which further contaminate the products derived from them, such as milk and meat-based products. Therefore, sensitive and robust identification, detection, and quantification methods along with efficient management and control measures are crucial. Spectrometric and spectroscopy techniques are quite sensitive and lead to better detection of the toxin in the food products. Control and preventive measures during harvesting, storage and transportation are found to be effective in managing the production of such toxins. This review insight on the occurrence, chemistry, biosynthesis, effects on human health and agriculture, detections, management, and control strategies of ochratoxins.
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•Ochratoxins are produced by Aspergillus and Penicillium spp.•Contaminations of various food and feed occur in crops during pre- and post-harvest.•Contaminated cereals and cereal-based products are consumed by both humans and animals.•Ochratoxins pose serious health issues like neurotoxicity and carcinogenesis.•Management strategies are required for the safety and security of food and feed.
Since the emergence of the first cases in Wuhan, China, the novel coronavirus (2019-nCoV) infection has been quickly spreading out to other provinces and neighboring countries. Estimation of the ...basic reproduction number by means of mathematical modeling can be helpful for determining the potential and severity of an outbreak and providing critical information for identifying the type of disease interventions and intensity. A deterministic compartmental model was devised based on the clinical progression of the disease, epidemiological status of the individuals, and intervention measures. The estimations based on likelihood and model analysis show that the control reproduction number may be as high as 6.47 (95% CI 5.71-7.23). Sensitivity analyses show that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with the effect of travel restriction adopted by Wuhan on 2019-nCoV infection in Beijing being almost equivalent to increasing quarantine by a 100 thousand baseline value. It is essential to assess how the expensive, resource-intensive measures implemented by the Chinese authorities can contribute to the prevention and control of the 2019-nCoV infection, and how long they should be maintained. Under the most restrictive measures, the outbreak is expected to peak within two weeks (since 23 January 2020) with a significant low peak value. With travel restriction (no imported exposed individuals to Beijing), the number of infected individuals in seven days will decrease by 91.14% in Beijing, compared with the scenario of no travel restriction.
With the acceleration of China's economic integration process, enterprises have gained greater advantages in the fierce market competition, and gradually formed the trend of grouping and large-scale. ...However, as the scale of the company increases, the establishment of a branch also causes many problems. For example, in order to obtain more benefits, the business performance of the company can generate false growth, resulting in financial and operational risks. This paper analyzed the current situation and needs of enterprise financial control from two aspects of theory and practice, combined with specific engineering projects, taking ZH Group as an example, according to the actual situation of the enterprise. The article first introduces the basic situation of the enterprise; Then, the financial control strategy was designed, and different modules were designed to achieve financial control; Afterwards, use a reverse neural network to evaluate the effectiveness of financial management and risk warning; Relying on particle swarm optimization algorithm to seek the optimal solution and applying it to financial management and risk warning, in order to improve the level of introspection and risk management in decision-making. Finally, the value of computer intelligence algorithms in financial big data management is evaluated by constructing a financial risk indicator system. Through the analysis of enterprise financial management, the total asset turnover rate of ZH Group decreased by 0.39 times in 5 years. After 5 years of adjustment of the company's business, the company's overall operational capabilities still needed to be improved, and the company's comprehensive business capabilities also still needed to be improved. Therefore, the application of intelligent algorithms for financial control is very necessary.
Digital twin technology is considered as a key technology to realize cyber-physical systems (CPS). However, due to the complexity of building a digital equivalent in virtual space to its physical ...counterpart, very little progress has been achieved in digital twin application, especially in the complex product assembly shop-floor. In this paper, we propose a framework of digital twin-based smart production management and control approach for complex product assembly shop-floors. Four core techniques embodied in the framework are illustrated in detail as follows: (1) real-time acquisition, organization, and management of the physical assembly shop-floor data, (2) construction of the assembly shop-floor digital twin, (3) digital twin and big data-driven prediction of the assembly shop-floor, and (4) digital twin-based assembly shop-floor production management and control service. To elaborate how to apply the proposed approach to reality, we present detailed implementation process of the proposed digital twin-based smart production management and control approach in a satellite assembly shop-floor scenario. Meanwhile, the future work to completely fulfill digital twin-based smart production management and control concept for complex product assembly shop-floors are discussed.
The use of Space Division Multiplexing (SDM) technology in Elastic Optical Networks (EONs) is a promising solution to improve the transport capability and flexibility required by next-generation ...applications. In this work, we have illustrated that Ant Colony Optimization (ACO) algorithms can be incorporated into the network control plane and associated with a crankback mechanism to provision and restore lightpaths in a fully distributed manner. In effect, by tackling the challenging Routing, Modulation, Spectrum, and Space Assignment (RMSSA) problem, ACO algorithms can address the inter-core crosstalk and spectrum fragmentation that may limit the potential of the SDM-EON. By comparing different levels of resource state accuracy at the control plane, the simulation results demonstrate the superior performance of the ACO algorithms compared to routing algorithms based on a centralized control plane with a link-state routing protocol, showcasing lower bandwidth blocking rate, comparable restorability, controlled crosstalk levels, and higher scalability, all achieved without a significant increase in setup and restoration times.
Promoting the downscaling and integration of zonal management and control of various environmental pollution sources is an effective way to systematically deal with the current high-intensity and ...complex environmental problems. Through single-factor and comprehensive pollutant emission intensity evaluation and cluster analysis, we built a full-coverage and cross-scale environmental spatial management and control system for pollution sources, then proposed environmental zoning patterns and pollution control strategies at three scales in the Yangtze River Delta (YRD), China. At the grid scale, the reclassified 7 types of pollution source spaces can be divided into 5 levels based on pollution emission intensity, and the most urgent environmental control subjects can be determined accordingly. Up to the county scale, combined with emission intensity and regional functions, 305 counties can be divided into 5 control intensity zones, which directly correspond to different environmental control intensity, requirements and policies. Finally, at the city scale, 41 cities can be clustered into 7 pollution control zones, which are classified and named as the three-level form of geographic location, development orientation and pollution source characteristics. Fully using the zoning units at different scales of cities, counties and grids can break the limitation of inherent administrative boundaries and allow environmental integration policies to be implemented across departments and regions, also let differentiated policies be more accurately implemented to different administrative levels and pollution source, and then truly improve the efficiency of environmental management.
•Geographical spatial structure affects environmental function benefit.•Downscale control system improves environmental management efficiency.•Controlling pollution source spaces through multi-scale zoning.•Inter-city integration zoning breaks the limitation of administrative powers.•Differentiated zoning within county improves the matching of environmental policies.
Fluctuations in arrival rates significantly affect the performance of traffic signal controls. In this paper, we propose an arrival-based distributed control algorithm based on the backpressure ...control framework, and show that this arrival-based backpressure (ABP) algorithm preserves the attractive features of backpressure control, including queue mitigation and global stability. Moreover, numerical results show that the ABP algorithm outperforms the fixed, actuated, and original backpressure signal controllers in low, medium, and heavy loading demand levels in increasing throughput, reducing queue length and waiting time.The benefits are evident under periodic traffic scenarios.
A systematic methodology for the real-time improvement of the overall efficiency of applications using hydraulic servo-axes is presented. The proposed methodology introduces three modules: a ...hydraulic actuator load estimator, a hydraulic energy optimizer and a controlled hydraulic power supply; these are discussed at the theoretical and application level. The proposed approach reduces the power losses across the main elements of the hydraulic circuit, leading to high energy savings and introducing a new guideline on managing and controlling the servo hydraulic actuator. The methodology is applicable to any application using hydraulic servo-axis systems, and therefore it is not tailored to a particular field. Its performances have been evaluated in different industrial case studies (a blanking press, a drawing press and a die-casting plant) through numerical simulations. Conspicuous energy savings, ranging between 59% and 88%, have been obtained in simulation, suggesting that a significant carbon footprint reduction for energy-intensive hydraulic machinery is achievable in a wide range of applications.
•Systematic methodology for the real time improvement of the overall efficiency of a hydraulic servo-axis.•Reduction of the power losses across the main elements of the hydraulic circuit, leading to high energy savings.•High bandwidth controlled hydraulic power supply.•The methodology applies to any application using hydraulic servo-axis systems, and therefore, it is not tailored to a particular field.•Its performances have been evaluated through numerical simulations in different industrial case studies.
In order to improve the risks management and control ability of coal chemical enterprises, this paper studies the dynamic risks management and control model of coal chemical enterprises and develops ...the supporting application software. A dynamic risk classification control algorithm for coal chemical enterprises is constructed by combining the optimized neural network with a control chart. By analyzing the control chart, the optimized neural network is used to predict and early warn the risk development trend of enterprises, and optimize coal chemical enterprises' process flow. Based on dynamic risks hierarchical management and control, the matching application tool, “dynamic risks hierarchical management and control system” is developed. The software was applied in Hongxing company in September 2017, which was developed by C/S mode, and the server developed “Webservice” to connect SQL Server and phone. The system's real time operation through the mobile phone is fast and straightforward, which realizes the dynamic risk classification management and control of coal chemical enterprises, and achieves good results.
•The dynamic risks hierarchical management and control method is constructed.•The risks hierarchical management and control system is designed.•The research is applied experimentally in the coal chemical enterprises.
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