High Volume Production Research Articles

Ecological risk assessment of p-toluidine in freshwater, sediment, and soil media.

Para-toluidine (p-toluidine) is a high production volume chemical, of which about 5,000 tons/year are imported into Korea as of the 2018 registration. This substance is mainly used as an intermediate in the manufacture of paints, azo dyes, and pigments. In this study, an ecological risk assessment of p-toluidine was performed to investigate the risk to the environment assuming the worst-case exposure scenario. Ecotoxicity data was collected from the literature and the predicted no effect concentration (PNEC) was derived. The predicted environmental concentration (PEC) was calculated using the SimpleBox Korea v2.0 model. Hazard quotient (HQ) was calculated based on PEC and PNEC. The concentration of p-toluidine was measured in soil samples from workplaces with a HQ exceeding 1 to verify the results of modeling. PNECs for surface water, sediment, and soil were 0.00022 mg/L, 0.0025 mg/kg (dw), and 0.00037 mg/kg (dw), respectively. Based on regional-scale PEC, the HQ of freshwater, sediment, and soil media were all less than 1, but the HQ exceeded 1 at some local sites. Based on the fact that the measured environmental concentration in soil samples around the workplace is below the limit of detection and that all waste is incinerated at the actual workplace, p-toluidine is not likely to pose a high risk to the environment in Korea.

A Νew Heuristic Optimization Approach to the Single Hoist Cyclic Scheduling Problem

This paper introduces an innovative heuristic optimization approach, referred to as Optimization Approach-Single Hoist Cyclic Scheduling Problem (OA-SHCSP), which aims to minimize the cycle time of the Single Hoist Scheduling Problem (SHCSP). The effectiveness of this proposed heuristic is compared with a previously established heuristic, the Earliest Starting Time (EST). The comparison results reveal that the proposed OA-SHCSP heuristic consistently outperforms the EST heuristic in minimizing cycle time, particularly when more than two products are produced simultaneously. Moreover, as the number of part tasks soaked during a cycle increases, OA-SHCSP demonstrates significantly improved computational efficiency over the EST heuristic. The reduction in average cycle time achieved by OA-SHCSP ranges from 28.73% to 60.29%, underscoring its effectiveness and potential for application in high-volume production environments.

The Performance of Waste Marble Instead of Coarse Aggregate

Now a days we are faced with an important consumption and a growing need for aggregates because of the growth in industrial production, this situation has led to a fast decrease of available resources. On the other hand, a high volume of marble production has generated a considerable amount of waste materials; almost 70%of this mineral gets wasted in the mining processing and polishing stages which have a serious impact on the environment. The processing waste is dumped and threatening the aquifer. Therefore, it has become necessary to reuse these wastes particularly in the manufacture of concrete products for construction purposes. This experimental study presents the variation in the strength of concrete when replacing aggregates by waste marble from 0% to 100% in steps of 25%, 50%, 75% & 100%. M25 grade of concrete were taken for study of slump value is reducing for more % of replacing the stone dust. The compressive strength of concrete cubes at the age of 7, 14 and 28 days were obtained at room temperature. From test result it was found that the maximum compressive strength is obtained only at 50% replacement of coarse aggregate by waste marble at room temperature. This result gives a clear picture that waste marble can be utilized in concrete mixtures as a good substitute for coarse aggregate giving higher strength.

Quantitative analysis of green investments in European automotive companies: a digital reporting analysis

AbstractAutomotive companies are a major driver of the economy due to their high production volumes and extensive supply networks. However, the shift towards focusing on Environmental, Social, and Governance (ESG) aspects to comply with regulatory constraints and meet shareholder expectations presents significant challenges. This study addresses the need for transparency in green investments and their impact on CO2 emissions within the automotive sector. To achieve this, a sample of 22 listed European automotive companies were selected based on their digital financial reports (XBRL), as well as their annual sustainability reports. Key variables, including Scope 1, Scope 2, and Scope 3 emissions, were evaluated alongside three categories of corporate investments: tangible, intangible, and other long-term assets. A robust Analysis of Covariance (ANCOVA) model was employed to quantify the relationship between these investment activities and emissions. The results indicate a significant interaction effect on Scope 1 emissions, while the effects on Scope 2 emissions were not significant and Scope 3 emissions showed marginal results. These findings suggest that companies disclose green investments to mitigate reputational risks, offering insights into the relationship between financial and sustainability metrics in ESG reporting, while highlighting the importance of transparent reporting for achieving sustainability goals and enhancing comparability among companies. Graphical abstract

Unique thermal architecture integrating heliostat solar fields with a dual-loop power generation cycle employing thermoelectric; thermal/financial study and GA optimization

This study delineates the development of a solar energy system that leverages concentrated solar power (CSP) technology to supply both electricity and potable water for residential applications. The proposed thermal architecture uniquely integrates heliostat solar fields with a dual-loop power generation cycle, augmented by a seawater desalination system that employs reverse osmosis (RO) membranes. To bolster electricity production, a thermoelectric generator (TEG) has been incorporated into the system's design framework. A comprehensive analysis of the system has been performed, encompassing thermodynamic and economic evaluations. Furthermore, a parametric analysis has been executed to investigate the effects of critical parameters on the system's operational efficiency. The efficacy of the system was rigorously assessed through a case study that examined its capabilities for daily production outputs. This research, grounded in the analytical projections from Saudi Arabia and the favorable environmental conditions characteristic of the region, explores the operational performance of the system within this specific geographical context. The primary objective of this inquiry is to determine the ideal operational parameters by employing multi-criteria optimization methods tailored to the established system. Variations in compressor pressure ratios were found to significantly affect the performance of the Brayton cycle and the exergetic efficiency of the system, with optimal economic efficiency being realized at a specific pressure ratio. Furthermore, increasing the inlet temperatures in the organic Rankine cycle has been shown to improve system efficiency up to a certain limit, beyond which potential reliability issues could arise. The case study demonstrated that electricity generation peaks during the summer months, particularly in June, aligning with a high volume of freshwater production totaling 264,530 m³. The optimization efforts achieved an exergetic efficiency of 17.69 % and an overall cost of $359.58 per hour.

Bioactive Compounds of Sea Mustard (Undaria pinnatifida) Waste Affected by Drying Methods

Sea mustard (Undaria pinnatifida) is a brown macroalga extensively cultivated and consumed in South Korea. However, the high volume of seaweed production in the country results in substantial waste generation. To mitigate this issue, the bioactive compounds of sea mustard waste parts (sporophyll, root, and stem) were assessed under different drying conditions (freeze, oven, and microwave drying) to evaluate their potential as functional ingredients. The sporophyll contained the highest levels of total chlorophyll (540.38 μg/g), fucoxanthin (165.87 μg/g), flavonoids (5.47 μg QE/g), phytomenadione (332.59 μg/100 g), and cobalamin (5.92 μg/100 g). In contrast, the root exhibited the highest antioxidant activities (DPPH: 1582.37 μg GAE/g; ABTS: 0.93 mg AA/g), total polyphenol (2718.81 μg GAE/g) and phlorotannin (4298.22 μg PGE/g) contents. Freeze drying achieved the best retention rates for most bioactive compounds, except for fucoxanthin, which was highest in microwave-dried samples. These results demonstrate the potential of sea mustard waste as a valuable source of bioactive compounds, with the retention of these compounds being influenced by drying methods, depending on the specific part of the seaweed.

Effects of Ply Misalignment in Material Characterization of Composite Laminates

Carbon fiber reinforced plastic (CFRP) parts find a rising number of applications as structural components. Therefore, new manufacturing technologies are developed, enabling high volume production of such parts. With those higher volumes, variation management during product design becomes more critical. While manufacturing variations in CFRP materials occur on different scales, detecting and considering those on the meso (ply) scale becomes more important. Thus, the question arises whether such variations can be detected with standardized testing methods. In this study, artificial fiber misalignment has been introduced into the outer plies of standardized tensile specimens to explore the influence of such variations on the mechanical properties. A simulation model was developed to identify these variations and the test results were used to calibrate and optimize the material parameters of the simulation model. The effects of the artificially induced variation were distinguishable in the test data as well as in the simulation models. Furthermore, the simulation models showed good agreement with the experimental data, which leads to the conclusion that the utilized measuring techniques are well suited to characterize the fiber misalignment. The developed simulation models can be used to investigate the effects of fiber misalignment within the product development process without the need for physical testing.

Machine learning prediction of the unconfined compressive strength of controlled low strength material using fly ash and pond ash

The sustainable use of industrial byproducts in civil engineering is a global priority, especially in reducing the environmental impact of waste materials. Among these, coal ash from thermal power plants poses a significant challenge due to its high production volume and potential for environmental pollution. This study explores the use of controlled low-strength material (CLSM), a flowable fill made from coal ash, cement, aggregates, water, and admixtures, as a solution for large-scale coal ash utilization. CLSM is suitable for both structural and geotechnical applications, balancing waste management with resource conservation. This research focuses on two key CLSM properties: flowability and unconfined compressive strength (UCS) at 28 days. Traditional testing methods are resource-intensive, and empirical models often fail to accurately predict UCS due to complex nonlinear relationships among variables. To address these limitations, four machine learning models—minimax probability machine regression (MPMR), multivariate adaptive regression splines (MARS), the group method of data handling (GMDH), and functional networks (FN) were employed to predict UCS. The MARS model performed best, achieving R2 values of 0.9642 in training and 0.9439 in testing, with the lowest comprehensive measure (COM) value of 1.296. Sensitivity analysis revealed that cement content was the most significant factor with obtaining R = 0.88, followed by water (R = 0.82), flowability (R = 0.79), pond ash (R = 0.78), curing period (R = 0.73), and fine content (R = 0.68), with fly ash (R = 0.55) having the least impact. These machine learning models provide superior accuracy compared to traditional methods, particularly in handling complex interactions between mix components. The proposed models offer a practical approach for predicting CLSM performance, supporting sustainable construction practices and the efficient use of industrial byproducts. The novelty of this study lies in the development of precise design equations for evaluating UCS, promoting both practical applicability and environmental sustainability.

Selecting alternative metals for advanced interconnects

Interconnect resistance and reliability have emerged as critical factors limiting the performance of advanced CMOS circuits. With the slowdown of transistor scaling, interconnect scaling has become the primary driver of continued circuit miniaturization. The associated scaling challenges for interconnects are expected to further intensify in future CMOS technology nodes. As interconnect dimensions approach the 10 nm scale, the limitations of conventional Cu dual-damascene metallization are becoming increasingly difficult to overcome, spurring over a decade of focused research into alternative metallization schemes. The selection of alternative metals is a highly complex process, requiring consideration of multiple criteria, including resistivity at reduced dimensions, reliability, thermal performance, process technology readiness, and sustainability. This Tutorial introduces the fundamental criteria for benchmarking and selecting alternative metals and reviews the current state of the art in this field. It covers materials nearing adoption in high-volume manufacturing, materials currently under active research, and potential future directions for fundamental study. While early alternatives to Cu metallization have recently been introduced in commercial CMOS devices, the search for the optimal interconnect metal remains ongoing.

The Influence of Carbon Fiber on Crystallization and Morphology of Poly(Ether Ketone Ketone) Composites Towards High Rate Thermoplastic Manufacturing Processes

Recent interest in thermoplastic composites for aerospace applications is driven by the need for high-volume manufacturing of materials that display excellent mechanical, thermal, and solvent resistive properties. Specifically, a large component of the composite properties of thermoplastic composites are highly dependent on the crystalline fraction of the semi-crystalline polymer matrix of the reinforced system. This work investigates the melting behavior of poly (ether ketone ketone) (PEKK) and the influence of temperature and fiber on crystallization kinetics and morphology of (PEKK) composites utilizing, differential scanning calorimetry, Velaris-Sefaris modelling, and polarized optical microscopy (POM). Annealing temperatures of 380°C and above were required to fully erase crystalline ordering in the PEKK matrix. Furthermore, carbon fibers accelerated crystallization kinetics in PEKK at a range of temperatures observed via DSC, and Velaris-Sefaris modelling implied a shift from bulk to surface induced nucleation by the addition carbon fiber to the PEKK matrix, reducing activation energy of crystallization events. This nucleation behavior was visually confirmed through POM with observation of transcrystalline domains nucleated from the surface of a single carbon fiber.

The Influence of Carbon Fiber on Crystallization and Morphology of Poly(Ether Ketone Ketone) Composites Towards High Rate Thermoplastic Manufacturing Processes

Recent interest in thermoplastic composites for aerospace applications is driven by the need for high-volume manufacturing of materials that display excellent mechanical, thermal, and solvent resistive properties. Specifically, a large component of the composite properties of thermoplastic composites are highly dependent on the crystalline fraction of the semi-crystalline polymer matrix of the reinforced system. This work investigates the melting behavior of poly (ether ketone ketone) (PEKK) and the influence of temperature and fiber on crystallization kinetics and morphology of (PEKK) composites utilizing, differential scanning calorimetry, Velaris-Sefaris modelling, and polarized optical microscopy (POM). Annealing temperatures of 380°C and above were required to fully erase crystalline ordering in the PEKK matrix. Furthermore, carbon fibers accelerated crystallization kinetics in PEKK at a range of temperatures observed via DSC, and Velaris-Sefaris modelling implied a shift from bulk to surface induced nucleation by the addition carbon fiber to the PEKK matrix, reducing activation energy of crystallization events. This nucleation behavior was visually confirmed through POM with observation of transcrystalline domains nucleated from the surface of a single carbon fiber.

A Novel Landfill Liner Material for Solidified Lake Sediment Based on Industrial By-Product and Construction Waste: Engineering Behavior and Cr(VI) Breakdown Characteristics

Engineering sludge, industrial waste, and construction waste are marked by high production volumes, substantial accumulation, and significant pollution. The resource utilization of these solid wastes is low, and the co-disposal of multiple solid wastes remains unfeasible. This study aimed to develop an effective impermeable liner material for landfills, utilizing industrial slag (e.g., granulated blast furnace slag, desulfurized gypsum, fly ash) and construction waste to consolidate lake sediment. To assess the engineering performance of the liner material based on solidified lake sediment presented in landfill leachate, macro-engineering characteristic parameters (unconfined compressive strength, hydraulic conductivity) were measured using unconfined compression and flexible wall penetration tests. Simultaneously, the mineral composition, functional groups, and microscopic morphology of the solidified lake sediment were analyzed using microscopic techniques (X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy + energy dispersive spectroscopy). The corrosion mechanism of landfill leachate on the solidified sediment liner material was investigated. Additionally, the breakdown behavior of heavy metal Cr(VI) within the solidified sediment liner barrier was investigated via soil column model experiments. The dispersion coefficient was computed based on the migration data of Cr(VI). Simultaneously, the detection of Cr(VI) concentration in pore water indicated that the solidified sediment liner could effectively impede the breakdown process of Cr(VI). The dispersion coefficient of Cr(VI) in solidified sediments is 5.5 × 10−6 cm2/s–9.5 × 10−6 cm2/s, which is comparable to the dispersion coefficient of heavy metal ions in compacted clay. The unconfined compressive strength and hydraulic conductivity of the solidified sediment ranged from 4.90 to 5.93 MPa and 9.41 × 10−8 to 4.13 × 10−7 cm/s, respectively. This study proposes a novel approach for the co-disposal and resource utilization of various solid wastes, potentially providing an alternative to clay liner materials for landfills.

Low-cost, high-volume, manufacturable 0.88 NA multi-wavelength diffractive lens array for optical document security

We design, manufacture, and characterize a high-numerical-aperture (NA=0.88, f/0.27), multi-wavelength (480 nm, 550 nm, and 650 nm) multilevel diffractive microlens array (MLA). This MLA achieves multi-wavelength focusing with a depth of focus (DoF) twice the diffraction-limited value. Each microlens in the array is closely packed with a diameter of 70 µm and a focal length of 19 µm in air. The MLA is patterned on one surface of a polymer film via UV casting, positioning the focal plane at the distal end of the polymer film. Each microlens focuses light at three design wavelengths into a focal spot with an estimated FWHM of ∼310nm. By placing this MLA directly on a standard high-resolution banknote print (minimum feature width of 10–15 µm), we demonstrate color-integral imaging for anti-counterfeiting. In contrast, refractive MLAs cannot achieve high-NA, multi-wavelength focusing or extended DoF. The extended DoF of our MLA ensures reliable performance despite variations in the polymer film’s thickness. Our MLA, produced via UV casting, enables extremely low-cost, high-volume production, making it ideal for flat optics in banknotes and document security.

Mechanical properties and chemical microscopic characteristics of all-solid-waste composite cementitious materials prepared from phosphogypsum and granulated blast furnace slag

Industrial wastes, such as phosphogypsum, are characterized by high production and accumulation volumes, and significant pollution. A high-performance, all-solid waste, phosphogypsum-based composite cementitious material (PCCM) was developed by using a hybrid ball milling method and thermal activation to stimulate various industrial wastes. Optimization of rationing was analyzed using extreme variance, standard variance, and multiple regression models. The macro-engineering parameters of PCCM were evaluated through flexural and compressive tests. The mineralogical composition, functional groups, micro-morphology, and molecular structure of PCCM were examined through micro-testing. When the mass ratio of Ball milled calcined phosphogypsum (BCPG) to granulated blast furnace slag (GGBS) is 1.2:1, with a 4 % addition of calcium oxide and a water-cement ratio of 0.4, the 28-day flexural and compressive strengths, as well as the softening coefficients, of PCCM can reach 7.27 MPa, 40.1 MPa, and 0.922, respectively, closely matching the performance of C42.5 cement. Under the synergistic effects of the hydration reaction and an alkaline environment, the CaSO4 in the PCCM system hydrated and crystallized to produce gypsum-phase crystals, enhancing early strength properties by 60–174 %. As hydration continued, SO42- reacted with silicon and aluminum oxides, prompting secondary hydration of GGBS, and increasing AFt and C-(A)-S-H in the system. This research offers a new approach for the co-disposal and resource utilization of various solid wastes while identifying a cementitious material that can replace traditional cement in practical engineering applications.

A novel FuseDecode Autoencoder for industrial visual inspection: Incremental anomaly detection improvement with gradual transition from unsupervised to mixed-supervision learning with reduced human effort

The industrial implementation of automated visual inspection leveraging deep learning is limited due to the labor-intensive labeling of datasets and the lack of datasets containing images of defects, which is especially the case in high-volume manufacturing with zero defect constraints. In this study, we present the FuseDecode Autoencoder (FuseDecode AE), a novel reconstruction-based anomaly detection model featuring incremental learning. Initially, the FuseDecode AE operates in an unsupervised manner on noisy data containing predominantly normal images and a small number of anomalous images. The predictions generated assist experts in distinguishing between normal and anomalous samples. Later, it adapts to weakly labeled datasets by retraining in a semi-supervised manner on normal data augmented with synthetic anomalies. As more real anomalous samples become available, the model further refines its capabilities through mixed-supervision learning on both normal and anomalous samples. Evaluation on a real industrial dataset of coating defects shows the effectiveness of the incremental learning approach. Furthermore, validation on the publicly accessible MVTec AD dataset demonstrates the FuseDecode AE's superiority over other state-of-the-art reconstruction-based models. These findings underscore its generalizability and effectiveness in automated visual inspection tasks, particularly in industrial settings.

Structural and electrical characterization of phase evolution in epitaxial Gd2O3 due to anneal temperature for silicon on insulator application

In this work, we understand the post-deposition anneal temperature effects on structural and electrical (leakage current and trap density) properties of epitaxial Gd2O3 film grown on Si (111) substrate using a cost-effective and High-Volume Manufacturing capable radio frequency sputtering method. It is found that the Rapid Thermal Annealing (RTA) at an optimum temperature of 850 °C enhances the crystallinity of the cubic phase in film. However, at higher RTA temperatures (>900 °C to 1050 °C), Si out-diffusion in Gd2O3 film is manifested as the reason for phase evolution towards the amorphous phase. The electrical characterization shows the film's low leakage current density of 100 nA/cm2. Moreover, increased breakdown voltage and field are observed with increasing RTA temperature. The frequency-dependent Capacitance-Voltage analysis shows a parallel shift accompanied by a kink at a lower frequency, indicating the presence of interface traps (Dit) with a range of time constants. After the forming gas annealing, a significant reduction in Dit is observed. The low leakage current density, low Dit and high crystallinity make Gd2O3 a promising candidate as a buried oxide in Silicon on Insulator MOSFETs.

Response and adaptation of Chlorella pyrenoidosa to 6PPD: Physiological and genetic mechanisms

The extensive contamination of the tire antidegradant N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD) in aquatic environments have raised concerns about its potential threats to aquatic organisms. Here, the responses of green algae Chlorella pyrenoidosa (C. pyrenoidosa) to 6PPD exposure were investigated for the first time. The growth of C. pyrenoidosa experienced three sequential phases, including inhibition, recovery and stimulation. Physiological and transcriptome analysis suggested that the growth inhibition was associated with the suppressed nitrogen assimilation and amino acid biosynthesis pathways, among which nitrate transporter (NRT) 2.1 was a key target of 6PPD. Molecular docking revealed the steadily binding of 6PPD to the substrate entry region of NRT 2.1 via hydrogen bonds and π − cation interaction, blocking the acquisition of extracellular inorganic nitrogen. Along with the removal of 6PPD through abiotic processes and biodegradation, an adaptive metabolic shift in cells not only facilitated growth recovery but also triggered a compensatory stimulation phase. With regard to microalgal adaptation, upregulated DNA replication and repair pathways served to maintain the integrity of the genetic information, enhanced photosynthesis cascades and central carbon metabolism improved carbon flux and energy conversion to microalgal biomass, recovered amino acid biosynthesis produced essential proteins for multiple metabolisms. The results provide new insights into microalgal molecular responses to 6PPD exposure, facilitating a better understanding of ecological consequences of 6PPD in the environment.

Advancing high-volume GaN manufacturing: precision simulation of electrical and geometrical deviations through current spreading

Abstract Manufacturing process deviations pose significant challenges in GaN manufacturing especially when modern technologies demand extreme chip densities. More than a thousand of each of three distinct GaN-based flip-chips were manufactured where the standard deviations of the measured voltages ranged from 13 to 23 mV. By integrating Monte Carlo and finite element methods in the simulations which relies on the theoretical models, the results were validated by comparing the voltage measurements of the three thousand manufactured chips. Validation was even successful considering the voltage deviations of the three distinct designs equivalently, i.e., affected the geometrical and electrical properties in each wafer. In addition, comparing the three designs, Chip A emerged as the optimal choice for low current resistivity. Looking ahead, our theoretical modeling and simulation hold promise for high-accuracy predictions in high-volume GaN-based chip manufacturing, enhancing reliability and performance.

Unveiling spatiotemporal distribution, partitioning, and transport mechanisms of tire additives and their transformation products in a highly urbanized estuarine region

Numerous tire additives are high-production volume chemicals that are used extensively worldwide. However, their presence and partitioning behavior remain largely unknown, particularly in marine environments. This study is the first to reveal the spatiotemporal distribution, multimedia partitioning, and transport processing of 22 tire additives and their transformation products (TATPs) in a highly urbanized estuary (n = 166). Nineteen, 18, and 20 TATPs were detectable in water, suspended particulate matter (SPM), and sediments, respectively, with total levels of 59.7–2021 ng/L, 164–6935 ng/g, and 4.66–58.4 ng/g, respectively. The multimedia partitioning mechanisms of TATPs are governed by their molecular weight, hydrophobicity, and biodegradation rate. Mass inventories coupled with model simulations have revealed that substantial quantities of TATPs accumulate within estuarine environments, and these compounds can be continuously transported into the ocean, particularly during the wet season. According to the multi-criteria evaluation approach, four and three TATPs were identified as high-priority pollutants during the dry and wet seasons, respectively. Unexpectedly, N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine quinone was only listed as a medium-priority pollutant. This study underscores the importance of marine surveillance and advocates for particular attention to these ubiquitous but underexplored TATPs in future studies.

The efficiency of CUSUM schemes for monitoring the multivariate coefficient of variation in short runs process

Current monitoring technologies emphasize and address the issue of monitoring high-volume production processes. The high flexibility and diversity of current industrial production processes make monitoring technology for small batch processes even more important. In multivariate process monitoring, a broader applicability exists in multivariate coefficients of variation (MCV) based monitoring schemes due to the lower restriction of the process. In view of the effectiveness of MCV monitoring and with the aim to achieve further performance improvement of current MCV monitoring schemes in a finite horizon production, we additionally introduce two one-sided cumulative sum (CUSUM) MCV schemes. In the case of deterministic and random shifts, the design parameters of the proposed schemes are obtained via an optimization procedure designed by the Markov chain method and the corresponding performance is analysed based on different run length (RL) characteristics, including the mean and the standard deviation. Simulation comparisons with existing exponentially weighted moving average (EWMA) MCV schemes show that the proposed CUSUM MCV schemes are more efficient in monitoring most of the shifts, including the deterministic and random shifts. Finally, to demonstrate the benefits of the new monitoring schemes, a comprehensive case study on monitoring a steel sleeve manufacturing process is conducted.