Factory System Research Articles

A two-stage stochastic programming model for comprehensive risk response action selection: A case study in Industry 4.0

Effective project risk management is critical in environments where both micro-level and macro-level risks are present. Traditional models often focus on micro-level risks, neglecting broader macroeconomic uncertainties such as geopolitical instability and supply chain disruptions. This research introduces a two-stage stochastic programming model designed to optimize the selection of Risk Response Actions (RRAs) under uncertainty while addressing both types of risk. The model incorporates “here-and-now” decisions at the planning stage and “wait-and-see” decisions as uncertainties unfold, enabling adaptive risk management throughout the project lifecycle. To solve the model efficiently, we employ an evolutionary algorithm combined with Sample Average Approximation (SAA) to handle the computational complexity of multiple scenarios. The model is applied to a real-world case study involving the integration of IoT and ERP systems in a smart factory in Iran, a project characterized by significant macroeconomic and geopolitical risks. Our key contribution lies in providing a comprehensive risk response strategy selection model that simultaneously addresses micro- and macro-level risks while incorporating strategic flexibility through outsourcing decisions. The results demonstrate that our model outperforms traditional deterministic models, offering enhanced resilience against macro-level risks and improved project performance under uncertainty. These findings provide valuable insights for project managers aiming to increase resilience and adaptability in volatile environments. By integrating both internal and external risk factors, our model offers a robust tool for managing complex projects, enhancing decision-making and project outcomes in uncertain conditions

Protocols of Production: The Absent Factories of Digital Capitalism

Contrary to dominant theories of postindustrial society, this article advances an alternative account of digital capitalism that repositions the factory—so often associated with industrial manufacturing—as a defining yet largely overlooked feature of the internet economy. I pursue this claim by interpreting data centers and microwork platforms as digital embodiments of the factory system through a historical theory of the factory model that reconstructs the consistent mechanisms of control and extraction that have distinguished factories as consolidated infrastructures of production since their inception. I define these “protocols of production” as formal rules deployed by a combination of technological systems, spatial arrangements, and management regimes devised to fragment tasks, discipline workers, and supervise production. By probing the socioeconomic consequences of the factory’s algorithmic redeployment and adaptation to global data production, I contend that these absent factories have amplified alienation and precarity as structural social qualities of the digital labor process.

The Main Controlling Factors of the Development and Extinction of ' Carbonate Factory '

Building upon the profound foundation of previous research on carbonate factories, this paper systematically organizes the classification system of carbonate factories and delves into the primary controlling factors of their demise, thereby providing a more precise portrayal of the diverse facets and intricate evolution of carbonate factories throughout geological history. Based on carbonate rock types, sedimentary environment characteristics, the dominant agents in the construction process, deposition and precipitation patterns, as well as oceanographic conditions, the carbonate factories are categorized into five major groups, each of which is comprehensively described. Furthermore, this paper summarizes six key controlling factors: fluctuations in nutrient levels, anoxic events, tectonic activities, massive inputs of terrestrial materials, mass extinctions of organisms, and significant changes in sea level. It delves into how these factors, acting either independently or synergistically, lead to the demise of carbonate factories, elaborating on the corresponding processes and mechanisms in detail.

Next-generation AMA1-based plasmids for enhanced heterologous expression in filamentous fungi.

Episomal AMA1-based plasmids are increasingly used for expressing biosynthetic pathways and CRISPR/Cas systems in filamentous fungi cell factories due to their high transformation efficiency and multicopy nature. However, the gene expression from AMA1 plasmids has been observed to be highly heterogeneous in growing mycelia. To overcome this limitation, here we developed next-generation AMA1-based plasmids that ensure homogeneous and strong expression. We achieved this by evaluating various degradation tags fused to the auxotrophic marker gene on the AMA1 plasmid, which introduces a more stringent selection pressure throughout multicellular fungal growth. With these improved plasmids, we observed in Aspergillus nidulans a 5-fold increase in the expression of a fluorescent reporter, a doubling in the efficiency of a CRISPRa system for genome mining, and a up to a 10-fold increase in the production of heterologous natural product metabolites. This strategy has the potential to be applied to diverse filamentous fungi.

A human-centric methodology for the co-evolution of operators’ skills, digital tools and user interfaces to support the Operator 4.0

The concept of Operator 4.0 has been recently defined to evolve the modern industrial scenarios by defining a knowledge sharing process from/to operators and industrial systems, creating personalized skills, and introducing digital tools towards socially sustainable factories. In this context, dynamic and adaptive user interfaces can make humans part of the intelligent factory system, supporting human work contextually and providing specific contents when needed, preserving the human wellbeing. This paper defines a human-centric methodology for the symbiotic co-evolution of operators’ skills, assistive digital tools and user interfaces, developed within the Horizon Europe project titled “DaCapo - Digital assets and tools for Circular value chains and manufacturing products”. The project focuses on defining a new set of human-centric digital tools and services for the manufacturing industry capable of boosting the application of circular economy (CE) throughout the manufacturing value chains. The proposed methodology can link the specific needs of an industrial case to the definition of the most proper assistive digital tools and functionalities to drive the design of adaptive, proactive user interfaces for the Operator 4.0. The method has been applied and validated on one of the project use cases, involving a manufacturing company operating in warehousing and logistics.

Development of Data Transmission Functionality for Smart Factory System

Development of Data Transmission Functionality for Smart Factory System

Factorial Mating system Analysis for Several Lines and Their Hybrids in Maize (Zea mays L.)

Factorial Mating system Analysis for Several Lines and Their Hybrids in Maize (Zea mays L.)

Securing Your Eggs in Multiple Baskets — Assuring a Resilient and Secure Supply Chain

AbstractThe global supply chain is a complex system of systems made up of and relying on other complex systems of systems (SoS) to achieve its goals. To take a typical example, Enterprise A is supplied essential parts on a regular basis to manufacture its products. To place the order requires global financial systems, integrated email systems, the internet, multiple telecommunications systems, and supply software provided by large companies. To deliver the parts may require air and maritime transportation systems, the rail network, interstate highway systems, road haulage companies, state and local transportation systems and so forth. When any of these complex systems fail, the impact can be global, and the results catastrophic. Recent examples include the shortage of Personal Protective Equipment (PPE) during the COVID pandemic, computer chip shortages delaying the assembly and sales of cars, and, most recently, the baby formula shortage. These were due to disruptions in the supply chain caused by an overreliance on single sourced suppliers who failed to deliver, transportation disruptions, outsourcing of critical parts, supplies, medicines to distant countries, and/or an overreliance on “Just In Time” for inventory management. This is the case of placing too many eggs in too few baskets, and often just one basket. Counterfeit or substandard parts and products can enter the supply chain via graft, breaks in chain of custody, or carelessness. This has included critical mechanical parts on aircraft, chips containing spyware, and substandard or out of date medicines substituted for the real thing resulting in serious illness and death. This complex SoS needs to be examined, studied, and understood in the same way as a mission critical system; threats, vulnerabilities, and risks need to be identified and mitigated and assurance cases defined to ensure a solid and reliable supply chain. This paper will look at the supply chain of an example factory system to determine how some of these problems can be predicted, prevented, mitigated, and solved using the UAF, RAAML and assurance case techniques.

Ameliorated Morpho-Physiological Response of Stevia Under the Influence of Variable LEDs Inside Plant Factory System

Ameliorated Morpho-Physiological Response of Stevia Under the Influence of Variable LEDs Inside Plant Factory System

A fixed‐frequency second‐order generalized integrator phase‐locked loop‐based phase synchronization control in multisegment wireless power transfer systems

SummaryMultisegment wireless power transfer (MSWPT) technology provides a solution to the challenges of dust‐free environments and automation faced by automated material handling systems (AMHS) in current semiconductor wafer factories. However, variations in track current frequency and phase offset on the transmitting side of the MSWPT technology may lead to significant deficits in energy transmission capability. This paper introduces a method based on the fixed‐frequency second‐order generalized integrator phase‐locked loop (FFSOGI‐PLL) structure for frequency and phase synchronization among multiple transmitters in a MSWPT system. By synchronizing the track currents of multiple transmitters, this method significantly enhances the energy harvesting capacity of the H‐type pickup in the overhead hoist transport (OHT) system, ensuring stable voltage at the receiver (Rx) load. Both theoretical simulations and experiments confirm that the proposed method can effectively capture the phase difference of track current and achieve frequency locking and phase tracking. Building on this theoretical foundation, we constructed three transmitter (Tx) systems and a 1.5 kW Rx equipped with an H‐type pickup. This setup is capable of real‐time monitoring and phase‐synchronization control of track currents with varying phase offsets. The results convincingly demonstrate the strong performance and stability of the proposed method.

Analysis of Fluid Pressure Drop through a Globe Valve using Computational Fluid Dynamics and Statistical Techniques

Fluid mechanics plays a crucial role in everyday life, enabling the selection of accessories, materials, and various components essential for a system through which fluid flows. Pressure drop stands out as one of the most relevant factors in the design of fluid flow systems. However, analytical and experimental physical methods can increase these analyses' costs and time. Hence, in this study, statistical tools are employed to carry out specific experiments supported by numerical fluid simulation, aiming to comprehend the pressure drop behavior in a fluid as it passes through a globe valve. This valve, in turn, possesses distinct operating and manufacturing characteristics. The methods employed encompass a complete factorial system of response surface as support to construct the experimental design path through computational fluid dynamics. Among the key findings, it is demonstrated that, for systems with relatively low flow rates, the valve opening percentage does not exhibit a significant relationship with fluid pressure drop. Conversely, significant effects are observed for systems with relatively high flow rates regarding the valve opening percentage and pressure drop, reaching values of up to 73% pressure drop in this study. It can be inferred that the integration of statistical experimental design techniques and computational fluid dynamics constitutes a valuable resource for studying the pressure drop of a fluid passing through a system.

Response Two Cultivars of Chickpea (Cicer arietinum L) to Phosphate Fertilization Level and Bacterial Inoculum

The research was conducted during season 2020 in Al-Shallalat area, 5 km northeast of Mosul. The study included three factors, namely, the treatment of seed soaking with water and the bacterial inoculum, two local cultivars of chickpea: large seeds (Kabuli) and small seeds (Desi) and three levels of phosphate fertilization (zero, 50 kg, and 100 kg P2O5. h-1). The study was conducted according to the factorial experiment system, in (R. C. B. D) design. In three replication, some traits of plant are obtained such as: plant height (cm), the height of the first pod above the ground (cm), pod length (cm), number of seeds/ pod, number of pods/plant (total), number of pods/plant (full) number of pods cleavage (empty), percentage of yield, the weight of 100 seeds (g), biological yield (g/plant), Seed yield (g/plant) and harvest index. The results indicate a significantly excelled of the treatment of soaking with bacteria inoculum on the treatment of soaking with water for all the studied traits. And highly significantly excelled in most of the studied traits of Kabuli over Desi cultivar. Most of the binary and triple interactions recorded a significant difference between the bacterial inoculum and the seeds of the Kabuli cultivar.

Design and Analysis of an H-Type Pickup for Multi-Segment Wireless Power Transfer Systems

To tackle the complex wireless power supply requirements in the Automated Material Handling System (AMHS) of semiconductor wafer factories, this paper presents a design method for a magnetic coupling mechanism based on a Multi-Segment Wireless Power Transfer (MSWPT) system for dynamic wireless power supply in segmented track configurations. Firstly, the track is approached using Inductive Power Transfer (IPT) technology combined with an LCC-S resonant structure transmitter (Tx). Following this, the feasibility of the H-type pickup is assessed through magnetic and electrical circuit analyses, which leads to the preliminary determination of the pickup dimensions by means of finite element magnetic and thermal simulations. Furthermore, an analysis of the mutual inductance drop is conducted under various track structure parameters during track crossing and curve negotiation operation conditions. Secondly, a dual-coil winding method is proposed to reduce the insulation stress on the PCB board. Additionally, a method for calculating the wire length and a design process for the overall parameters of the pickup are derived. Finally, two Txs and a 1.5 kW power receiver (Rx) were designed to verify the mutual inductance fall under the aforementioned conditions. During low-speed full-load operations, a constant-voltage output was achieved through the proposed dual-loop PI control strategy, thereby meeting the requirements for a constant-voltage output in industrial applications.

Biosynthesis of apigenin glucosides in engineered Corynebacterium glutamicum.

Glucosylation is a well-known approach to improve the solubility, pharmacological, and biological properties of flavonoids, making flavonoid glucosides a target for large-scale biosynthesis. However, the low yield of products coupled with the requirement of expensive UDP-sugars limits the application of enzymatic systems for large-scale. C. glutamicum is a Gram-positive and generally regarded as safe (GRAS) bacteria frequently employed for the large-scale production of amino acids and bio-fuels. Due to the versatility of its cell factory system and its non-endotoxin producing properties, it has become an attractive system for the industrial-scale biosynthesis of alternate products. Here, we explored the cell factory of C. glutamicum for efficient glucosylation of flavonoids using apigenin as a model flavonoid, with the heterologous expression of a promiscuous glycosyltransferase, YdhE from Bacillus licheniformis and the endogenous overexpression of C. glutamicum genes galU1 encoding UDP-glucose pyrophosphorylase and pgm encoding phosphoglucomutase involved in the synthesis of UDP-glucose to create a C. glutamicum cell factory system capable of efficiently glucosylation apigenin with a high yield of glucosides production. Consequently, the production of various apigenin glucosides was controlled under different temperatures yielding almost 4.2 mM of APG1(apigenin-4'-O-β-glucoside) at 25℃, and 0.6 mM of APG2 (apigenin-7-O-β-glucoside), 1.7 mM of APG3 (apigenin-4',7-O-β-diglucoside) and 2.1 mM of APG4 (apigenin- 4',5-O-β-diglucoside) after 40 h of incubation with the supplementation of 5 mM of apigenin and 37℃. The cost-effective developed system could be used to modify a wide range of plant secondary metabolites with increased pharmacokinetic activities on a large scale without the use of expensive UDP-sugars.

Biosynthesis of Apigenin Glucosides in Engineered Corynebacterium glutamicum.

Glucosylation is a well-known approach to improve the solubility, pharmacological, and biological properties of flavonoids, making flavonoid glucosides a target for large-scale biosynthesis. However, the low yield of products coupled with the requirement of expensive UDP-sugars limits the application of enzymatic systems for large-scale. C. glutamicum is a Gram-positive and generally regarded as safe (GRAS) bacteria frequently employed for the large-scale production of amino acids and bio-fuels. Due to the versatility of its cell factory system and its non-endotoxin producing properties, it has become an attractive system for the industrial-scale biosynthesis of alternate products. Here, we explored the cell factory of C. glutamicum for efficient glucosylation of flavonoids using apigenin as a model flavonoid, with the heterologous expression of a promiscuous glycosyltransferase, YdhE from Bacillus licheniformis and the endogenous overexpression of C. glutamicum genes galU1 encoding UDP-glucose pyrophosphorylase and pgm encoding phosphoglucomutase involved in the synthesis of UDP-glucose to create a C. glutamicum cell factory system capable of efficiently glucosylation apigenin with a high yield of glucosides production. Consequently, the production of various apigenin glucosides was controlled under different temperatures yielding almost 4.2 mM of APG1(apigenin-4'-O-β-glucoside) at 25°C, and 0.6 mM of APG2 (apigenin-7-O-β-glucoside), 1.7 mM of APG3 (apigenin-4',7-O-β-diglucoside) and 2.1 mM of APG4 (apigenin-4',5-O-β-diglucoside) after 40 h of incubation with the supplementation of 5 mM of apigenin and 37°C. The cost-effective developed system could be used to modify a wide range of plant secondary metabolites with increased pharmacokinetic activities on a large scale without the use of expensive UDP-sugars.

The Growth and Tuber Yield of Potatoes (Solanum tuberosum L.) under Varying LED Light Spectrums in Controlled Greenhouse Conditions

Plant growing using light-emitting diodes (LEDs) in a controlled environment is a revolutionary and innovative idea, regardless of the external environmental disturbances. Studying the growth and tuber yield of potatoes (Solanum tuberosum L.) in an LED-based plant factory system is a relatively innovative concept. The current study was conducted in a plant factory to evaluate the effects of different LED spectral compositions on potato tuberization. Potato tuberization was analyzed under six different LED light spectral combinations with irradiances of 300 mol m−2 s−1, with natural light considered the control treatment. The findings stated that the L2 treatment (red70 + blue20 + white10) increased the plant height, branch number, and biomass accumulation, while photosynthetic pigments and photosynthetic activity increased significantly in L5 (red60 + blue20 + green10 + white10). Higher gibberellic acid (GA3) content was recorded in L1 (red70 + blue30), whereas the tuber number and tuber fresh weight were recorded in L3 (red70 + blue20 + green10) and L7 (natural light), respectively. On the other hand, a higher number of smaller-sized tubers were observed in L5, while L2 and L4 (red70 + blue20 + far-red10) resulted in a higher number of medium-sized tubers. In conclusion, a high proportion of red and blue light, along with white and far-red light, increased the plant height, branch number, plant biomass, and production of small- and medium-sized tubers. On the other hand, the inclusion of green light with red and blue enhanced the chlorophyll content, photosynthesis, and leaf expansion, and promoted the production of smaller-sized tubers. Finally, with regard to tuberization, the treatment using L4 followed by L2 outperformed the other treatments.

Research on Real Time Data Monitoring Method for Intelligent Factory Equipment Based on Ethernet Communication

<p>This article focuses on the production and processing of sleeve parts, using Ethernet as a data transmission medium to complete data collection and monitoring of typical intelligent factory processing workshops. Firstly, the layout design of the intelligent factory equipment layer, communication layer, and system application layer was completed. Then, unified management of standard and non-standard protocols was implemented for communication between different devices. Then, based on the sensors and sensor data used in each production process, a data collection scheme was designed, and finally, the data collection system was designed, Real time monitoring of data between various devices in the system can guide enterprise production.</p> <p> </p>

Optimization of ON-grid hybrid PV/wind system for a cement factory in Kuwait using HOMER pro software

Abstract The reliance on a single energy source leads to many problems, i.e. cost and unsustainable operation. Hybrid renewable energy systems (include more than one energy source) has been effectively shown as a feasible choice to overcome these problems. The main purpose of this research is to carry out a techno-economic optimization to minimize the size of the system with lower cost and higher reliability. This proposed ON-grid hybrid PV/wind energy system is designed to supply the electrical power of a cement factory in Kuwait. To achieve this purpose, the Hybrid Optimization of Electric Energy (HOMER Pro) software was utilized to carry out the optimization process. The results of this study show that the cost of electricity energy generated by the hybrid PV/wind energy system is equal to $0.082/kWh which is much lower when compared to the conventional fuel power plants in Kuwait which is approximately $0.12/kWh.

Understanding user resistance of smart factory adoption: a focus on small and medium-sized enterprises

PurposeThe purpose of this paper is to examine the resistance behavior of smart factories in small and medium-sized enterprises (SMEs). Drawing upon dual factor perspective, this study examines how two types of quality and perceived usefulness impact user resistance as enabling factors and how switching cost, skepticism, habit and inertia contribute to user resistance as inhibiting factors. Additionally, multi-group analysis is employed to compare small and medium enterprises.Design/methodology/approachPurposive sampling technique was employed to collect 460 Korean SMEs employees, consisting of 235 small enterprises and 225 medium enterprises. Partial least squares structural equation modeling was used for data analysis.FindingsThe results reveal that all three inhibiting factors, switching cost, skepticism and habit, are key antecedents of inertia. In small enterprises, skepticism has a greater impact on inertia, which in turn strongly affects resistance. Additionally, system quality is more crucial for small enterprises, whereas information quality holds more importance for medium enterprises in mitigating resistance. Moreover, when the implementation level of a smart factory is high, the effect of perceived usefulness on user resistance diminishes.Originality/valueThis study has revealed the importance of considering both enabling and inhibiting factors for the adoption of smart factory systems in the context of SMEs. Additionally, it has provided evidence that as the level of the smart factory system increases, the effect of perceived usefulness on user resistance decreases, thus making the transition to smart factory systems more challenging.

Assessing risk of AR and organizational changes factors in socio-technical robotic manufacturing

Technological changes such as the use of Augmented Reality (AR) along with the advent of new organizational changes such as digitalization are on the one hand positively changing the way of working but on the other hand they are introducing new risks, potentially leading to not only normal but also post-normal accidents. In our previous work, we have incrementally proposed a novel framework, called FRAAR, for risk assessment of AR-equipped socio-technical systems (i.e., systems integrating human, organizational and technical entities (such as AR)). We have also partly evaluated our framework via an industrial automotive study and by providing comparison and positioning with respect to other related works in a systematic literature review. In this paper, we conduct a new study to evaluate the applicability and effectiveness of our framework in a different domain. To do that, we choose a digitalized socio-technical factory system, focusing on the human–robot collaboration for a realistic diesel engine assembly task using AR-based user interface in an organization affected by organizational changes. Then, we design and execute our study to apply our framework and we discuss about the extent the conceptualizations provided by the framework are effective to capture the essential information for risk assessment in socio-technical robotic manufacturing, the extent the robotic safety standards are supported (to demonstrate the applicability of the framework in the robotic domain) and the extent of effectiveness of the risk assessment with respect to AR and organizational changes. Finally, we discuss about validity of our work and we provide our findings and intended future work.