Rate Of Products Research Articles

Research on the inerting mechanism of sucrose dust explosion by sodium bicarbonate

Sucrose dust is prone to explosion accidents during the production process. This research utilized sodium bicarbonate (NaHCO3) to prevent the explosion of sucrose dust. Based on the minimum ignition temperature of sucrose dust cloud (MITc), combined with thermogravimetric analysis-differential scanning calorimetry (TG-DSC) and pyrolysis-gas chromatography-mass spectrometry (PY-GCMS), the differences of combustion processes and combustion products between sucrose dust and sucrose-NaHCO3 mixed dust were comprehensively compared. Also, the mechanisms of sucrose dust explosion and NaHCO3 inerting sucrose dust were systematically studied. It showed that NaHCO3 powder contributed to a higher MITc of sucrose dust and activation energy of sucrose oxidation reaction, with a reduction in exothermic enthalpy and entropy changes. NaHCO3 interfered with the entire burning process of sucrose dust by playing an important role in physical inhibition, and producing sodium-containing compounds to capture free radicals from the bond breakage of sucrose. It limits the reaction pathway and progress of sucrose pyrolysis and therefore against burning. Additionally, the mass fraction and particle size of NaHCO3 impact the inerting ability by increasing the amount and accelerating the procedure rate of products, respectively. The increase in mass fraction works better in macroscopic phenomena, while the decrease in particle size is more significant in reaction kinetics and thermodynamic parameters.

Photoelectrothermocatalytic reduction of CO2 to glycol via Cu2S/MoS2-Vs octahedral heterostructure with synergistic mechanism

The defects and interface engineering are efficient approaches to adjust the physical and chemical properties of nanomaterials to enhance catalytic performance. In this study, we report a new MOFs-driven porous Cu2S/MoS2-Vs octahedral semiconductor with heterostructure and photothermal effect. The introduction of sulfur vacancies directly improves the adsorption performance of CO2, and the formation of heterostructure significantly increases the charge transfer rate. The C-penetrating material obtained from MOFs not only acts as an octahedral skeleton support, but also gives photothermal effects under photoelectric conditions. The formation rate of sole C2 products in photoelectrocatalytic CO2 reduction by using Cu2S/MoS2-Vs heterostructure is up to 52 μM·h−1·cm−2 equal to the total electron transfer rate of 541 μM·h−1·cm−2. The carbene mechanism and reaction pathways were proposed and verified by 13CO2 isotopic labelling and operando Fourier transform infrared (FT-IR) spectra. The important intermediates of *CO2−, *CO, *CHO and *CHO-CHO were identified by operando FT-IR spectra. In the comparative experiments, the photothermal electrons are beneficial to C2 products. DFT calculations indicate that the presence of S vacancies (Vs) reduces the energy barrier for product generation.

Assisting Healthier and More Sustainable Online Food Choices Through Digital Quality Signals: Exploring Preferences and Segments

The current paper contributes to signalling theory by demonstrating the importance of digital quality signals in influencing consumer preferences for sales and segmentation in the context of marketing fresh fish online. We conducted a choice-based conjoint analysis with a latent class segmentation to analyse the significance of digital quality signals compared to traditional attributes online. The analysis of 1,411 global consumers revealed that product rating was among the most important factors when purchasing fresh salmon fillets online. Latent class segmentation identified four distinct segments, the largest being ‘value for money’, where product rating and pricing were most important. The other segments were ‘environmentally friendly’, prioritising procurement methods and place of origin; ‘want it now’, where delivery was the most important factor; and ‘quality conscious’, which relied on three attributes – origin, delivery, and product rating. This study enhances understanding of the impact of socially mediated stimuli. It demonstrates the ability of digital quality signals to compensate for the absence of sensory evaluation in online store environments or deficiencies in knowledge or experience. The findings will benefit the food industry and online grocery retailers in promoting healthier and more sustainable products such as fish online.

Cu Promoted the Dynamic Evolution of Ni-Based Catalysts for Polyethylene Terephthalate Plastic Upcycling.

Upcycling plastic wastes into value-added chemicals is a promising approach to put end-of-life plastic wastes back into their ecocycle. As one of the polyesters that is used daily, polyethylene terephthalate (PET) plastic waste is employed here as the model substrate. Herein, a nickel (Ni)-based catalyst was prepared via electrochemically depositing copper (Cu) species on Ni foam (NiCu/NF). The NiCu/NF formed Cu/CuO and Ni/NiO/Ni(OH)2 core-shell structures before electrolysis and reconstructed into NiOOH and CuOOH/Cu(OH)2 active species during the ethylene glycol (EG) oxidation. After oxidation, the Cu and Ni species evolved into more reduced species. An indirect mechanism was identified as the main EG oxidation (EGOR) mechanism. In EGOR, NiCu60s/NF catalyst exhibited an optimal Faradaic efficiency (FE, 95.8%) and yield rate (0.70 mmol cm-2 h-1) for formate production. Also, over 80% FE of formate was achieved when a commercial PET plastic powder hydrolysate was applied. Furthermore, commercial PET plastic water bottle waste was employed as a substrate for electrocatalytic upcycling, and pure terephthalic acid (TPA) was recovered only after 1 h electrolysis. Lastly, density functional theory (DFT) calculation revealed that the key role of Cu was significantly reducing the Gibbs free-energy barrier (ΔG) of EGOR's rate-determining step (RDS), promoting catalysts' dynamic evolution, and facilitating the C-C bond cleavage.

Growth rate of pineapple production in India

Pineapple (Ananas comosus) is one of the most important tropical and subtropical fruit of Bromeliaceae family, cultivated almost one third part of the world. Pineapple takes almost 16 -22 months to mature for harvesting. The main objective of this paper is to analyzed the growth rate in area, production and productivity of pineapple in India as well as Karnataka. The time series data from 2002-03 to 2021-22 for the study. The results revealed that the area (1.94%), production (2.56%) and productivity (0.64%) showed that positive and significant at one per cent level of probability in India. In Karnataka, the growth rate of productivity (0.99%) showed that positive and significant at five per cent level of productivity due to area expansion. For area (0.14%) and production (1.04%) showed positive and non-significant. Whereas, Cuddy Della Valle index (CDVI) for area, production and productivity were 6.79, 7.66 and 3.76, respectively in India. In Karnataka, the Cuddy Della Valle index (CDVI) for area, production and productivity were 10.55, 22.37 and 8.78. The slight variation in productivityof pineapple in India are mainly because inadequate farm management techniques i.e., less use of chemical fertilizer, pesticides, improper suckers, inadequate knowledge and insufficient use of other input, which are the result of less production and productivity.

Export of fruits, vegetables and their products from India - A study on growth rate and instability index

The study aimed to analyze the growth rate and instability index for export of fruits, vegetables and products of fruits and vegetables from India. The present study based on the secondary data, data were collected from Agricultural and Processed Food Export Development Authority (APEDA). Compound annual growth rate analysis and cuddy della valle instability index were employed for analysis of growth rate and instability index of fruits, vegetables and products of fruits and vegetables from India. Here secondary data for fruits, vegetables and products of fruits and vegetables was collected for the period of 2006-07 to 2021-22. The results reveals that the CAGR for the export of fruits and vegetables in terms of quantity and value showed a positive and significant growth rate for potato (12.59 and 21.56%), watermelon (11.75 and 21.19%), green chilli (9.03 and 20.70%), other fresh vegetables (8.49 and 15.99%), grapes (8.18 and 18.70%), pomegranate (7.91 and 19.15%), oranges (7.30and 17.98%), garlic (7.26 and 17.61%) and other fresh fruits (7.06 and 16.54%), But mango shows negative growth rate of -5.26 per centin terms of quantity and the highest instability index showed for orangesat 75.53 and 74.42, respectively. For products of fruits and vegetables in terms of quantity and value the CAGR for the export of raisins (41.00 and 50.48%), potato (prepared and preserved) (36.85 and 40.64%), other vegetables products (betel leaves and nuts) (15.28 and 23.09%), processed fruits, juices and nuts (10.15 and 18.76%), onion (dried and powdered) (6.71 and 15.06%), processed vegetables (5.41 and 14.04%), fruits and vegetables seeds (4.79 and 16.93%), guar gum (4.73 and 8.32%), mango pulp (3.63 and 2.33%) and cucumber and gherkins (prepared and preserved) (1.03 and 8.71%). But walnuts shows negative and significant growth rate of -9.97 and -7.51per cent and the highest instability index showed for potato (prepared and preserved) and guar gum at 67.98 and 105.79, respectively. This conclude that there had been absolute growth rate due to increased fruits and vegetables production, growing international demand for fruits, vegetables and products of fruits and vegetables, competitive pricing in global market. By this India can continue to expand its presence in global market, boosting economic growth and benefiting farmers and stake holders across the agricultural value chain and reduce risk of export in future days.

Titanium carbide sealed cadmium sulfide quantum dots on carbon, oxygen-doped boron nitride for enhanced and durable photochemical carbon dioxide reduction

Despite great efforts that have been made, photocatalytic carbon dioxide (CO2) reduction still faces enormous challenges due to the sluggish kinetics or disadvantageous thermodynamics. Herein, cadmium sulfide quantum dots (CdS QDs) were loaded onto carbon, oxygen-doped boron nitride (BN) and encapsulated by titanium carbide (Ti3C2, MXene) layers to construct a ternary composite. The uniform distribution of CdS QDs and the tight interfacial interaction among the three components could be achieved by adjusting the loading amounts of CdS QDs and MXene. The ternary 100MX/CQ/BN sample gave a productive rate of 2.45 and 0.44 μmol g-1 h−1 for carbon monoxide (CO) and methane (CH4), respectively. This CO yield is 1.93 and 6.13 times higher than that of CdS QDs/BN and BN counterparts. The photocatalytic durability of the ternary composite is significantly improved compared with CdS QDs/BN because MXene can protect CdS from photocorrosion. The characterization results demonstrate that the excellent CO2 adsorption and activation capabilities of BN, the visible light absorption of CdS QDs, the good conductivity of MXene and the well-matched energy band alignment jointly promote the photocatalytic performance of the ternary catalyst.

Dynamic response characteristics of solid oxide cell stacks for seawater/CO2 co-electrolysis under strong fluctuation electricity

This work focused on the intermittent characteristics of renewable energy and studied the dynamic response characteristics of seawater/CO2 co-electrolysis on solid oxide cell stacks to produce syngas under strong fluctuation electricity conditions. The results showed that when using a strong fluctuating current density of 58.2–658.1 mA/cm2 to simulate wind turbines, the power variation of the solid oxide cell stack was almost in line with the simulated wind turbine power variation curve. The theoretical conversion rate of solid oxide cell stack electrolysis products is linearly related to the current density. The measured H2O+CO2 conversion rate is similar to the theoretical value, and the current variation hardly changes the H2/CO ratio in the exhaust gas. Therefore, solid oxide electrolysis cell stacks have strong adaptability to fluctuating electricity.

Processing complementary foods to reduce mycotoxins in a medium scale Tanzanian mill: A hazard analysis critical control point (HACCP) approach

Designing and implementing processing procedures for producing safe complementary foods in dynamic and unregulated food systems where common food staples are frequently contaminated with mycotoxins is challenging. This paper presents lessons about minimizing aflatoxins (AF) in groundnut flour and AF and/or fumonisins (FUM) in maize and groundnut pre-blended flour for complementary feeding in the context of a dietary research intervention in rural Tanzania. The flours were processed in collaboration with Halisi Products Limited (Halisi), a medium scale enterprise with experience in milling cereal-based flours in Arusha, Tanzania. Using a hazard analysis critical control point (HACCP) approach for quality assurance, two critical control points (CCPs) for AF in processing the pre-blended flour were identified: 1) screening maize before procurement, and 2) blending during the processing of each constituent flour. Blending of maize flour was also identified as a CCP for FUM. Visual inspection during screening and sorting were identified as important control measures for reducing AF, but these steps did not meet the criteria for a CCP due to lack of objective measurement and verifiable standards for AF. The HACCP approach enabled the production of low AF (<5 μg/kg) and FUM (<2 μg/g) flours with low rejection rates for the final products. The paper presents practical lessons that could be of value to a range of commercial processors in similar low- and middle-income contexts who are keen on improving food quality.

Optimization Scheme of Measuring Accuracy of Bearing Seat Size Based on Machine Vision

At present, the size measurement of industrial workpieces is mainly manual measurement and CMM measurement, which cannot meet the requirements of high precision, high efficiency and low error rate in industrial production at the same time. In order to solve the above problems, this paper uses monocular vision technology to propose an optimization scheme of workpiece size measurement accuracy based on machine vision, which takes the height and declination Angle between the camera lens and the workpiece as variables. Firstly, the image was captured by camera calibration correction, and morphological methods such as gray-scale, denoising, expansion and corrosion were used for image pre-processing. Secondly, features were extracted using double-threshold canny edge detection algorithm and connected domain algorithm. Finally, the bearing seat size was measured using the minimum external rectangle algorithm. The experiment shows that the higher the distance between the camera lens and the stage, the larger the error is when the image information can be collected completely. The greater the Angle between the center of the camera lens and the center of the workpiece, the greater the error; The device not only meets the precision requirements, but also has the advantages of fast response speed, which can meet the needs of industrial applications.

Surface modification of micronized calcite (CaCO3) with stearic acid via mechanical dry coating

In this study, the surface coating (modification) of micronized calcite (CaCO3, d50=135 μm) in a stirred media (bead) mill with stearic acid was investigated. As a result of 15 min grinding and 5 min coating experiments, a product with d50=2.15 μm and specific surface area of 3.21 m2/cm3 was obtained. The activation rate of this final product as an indicator of coating rate was 97.7%. According to the optimum coating results, the stearic acid rate was determined as 1%, the modification time was 7.5 min, the ball load was 900 g and the stirring speed was 600 rpm.

Pyridine N-induced intra-pore and interfacial dual-confined Pd0-Pdδ+ synergistic catalysis for ultra-stable dehydrogenation of dodecahydro-N-propylcarbazole

We developed nano Pd catalysts, encapsulated within carbon-nitrogen layers at both intra-pore and interfacial levels on SiO2, via in-situ thermolysis of metal-organic coordination compounds. The catalysts dehydrogenation efficacy is greatly influenced by thermolysis temperature and ligand-to-metal ratio. The Pd-C-N2/SiO2-600 catalyst notably achieved complete dehydrogenation of 12 H-NPCZ within 240 minutes, demonstrating exceptional stability over 10 cycles without significant degradation, highlighting its viability for commercial use. Characterizations revealed that the C-N layer integration improves Pd nanoparticle dispersion and reduces strong acid site formation on catalyst surface. This synergy between the C-N layer and Pd nanoparticles promotes the formation and stabilization of Pdδ+ species, optimizing them as adsorption sites for dehydrogenation with appropriate acid strength. Moreover, this interaction adjusts the electronic states of Pd0 active sites, optimizing adsorption dynamics for intermediates. This cooperative action between Pd0 and Pdδ+ significantly boosts the desorption rate of dehydrogenation products, substantially improving the catalysis performance.

Au@ZnS core–shell nanoparticles decorated 3D hierarchical porous TiO2 photocatalysts for visible-light-driven CO2 reduction into CH4

Hereby, the core–shell structured Au@ZnS nanoparticles were precipitated on three-dimensionally ordered macro-mesoporous TiO2 (Au@ZnS/3DOMm-TiO2) by GBMR/P method. The slow photon effect of 3DOM structure leads to increase the light trapping and absorption efficiency. The hierarchical porous structure improves the specific surface area of the carrier, providing a larger internal void for desorption of reaction products and additional activation sites for the CO2 reduction. In the all-solid Z-scheme system, electrons are transferred along the direction from TiO2 to Au and finally to the surface of ZnS is realized to participate in the reaction of CO2 reduction. Under irradiation of visible light, ternary Au@ZnS/3DOMm-TiO2-2 catalyst exhibits the highest catalytic activity for CO2 photoreduction with H2O, i.e., the formation rate and selectivity of CH4 product is 33.2 µmol g-1h−1 and 91.5 %, respectively. The design of Z-scheme heterojunctions on 3D macro-mesoporous oxide surfaces are expected to expand new ideas for the preparation of efficient photocatalysts.

Effect of n-C-S-H on Hydration and Reinforcement of Mineral Powder-Cement System at Low Temperatures.

This paper investigated the effect of nano-calcium silicate hydrate (n-C-S-H) on the early compressive strength of mineral powder-cement systems under low-temperature curing conditions (5 °C). The hydration mechanism of n-C-S-H in the mineral powder-cement system at different dosages was analyzed by combining it with XRD, DSC-TG, MIP, and other techniques. The results show that n-C-S-H significantly enhances the early compressive strength of the mineral powder-cement system under low-temperature curing conditions, with optimal results observed at a dosage of 1.0% (mass fraction). The XRD, DSC-TG, and MIP tests reveal that n-C-S-H promotes the hydration of the mineral powder cement, accelerates the generation rate of hydration products, reduces the porosity of the hardened mineral powder-cement slurry, and improves the system's density.

Determining the Best Rate of Blended NPKSZnB Fertilizer for Optimum Onion Yield and Yield Components in Northwestern Tigray, Ethiopia

Aim: The nutrient content of current fertilizer recommendations is unbalanced and is based on a very general and blanket recommendation for all soil and crop types, and their economic benefit is low. Therefore, this study was initiated to validate the recommendations regarding blended fertilizers applied to the soil and to identify the best fertilizer dose that ensures optimal yield and maximum economic return. Study Hypotheses: significance effect of blended NPKSZnB fertilizer on onion yield and yield components. Study Design: The experiment was designed using a randomized complete block design with three replications and seven treatments. Place and Duration of the study: The field experiment was conducted in the off-season of 2018 and 2019 in Tahtay Koraro (two farmers), and Laelay adyabo (two farmers) districts of in northern Ethiopia. Methodology: Seven treatments with NPKSZnB fertilizer rates (25, 50, 100, 150, 200, 250 and 300 kg·ha-1) were tested under irrigation conditions. Thus, for each plot nitrogen from Urea was applied at a rate of 150 kg ha-1. Surface soil samples were collected before planting onion harvesting at a depth of 0-20 cm to analyze selected soil chemical properties such as pH, extractable electric conductivity (ECe), cation exchange capacity (CEC), total nitrogen (TN), available P and exchangeable bases (K, Mg, Ca, and Na). Results: The application of different doses of NPKSZnB under irrigation conditions had a statistically significant (P &lt; 0.05) impact on onion phenology, yield and yield components. The highest average onion yield (10,329 and 19,196 kg ha-1) was obtained after applying compound fertilizer doses of 200 and 250 kg ha-1 in Teahtay Koraro and Laelay Adyabo districts, respectively. However, the use of NPKSZnB fertilizer at a dose of 100 and 50 kg ha-1 for onion cultivation under irrigated conditions in T/koraro and L/adyabo districts was found to be economically viable. Thus, growers in both districts should use NPKSZnB compound fertilizer at these rates for onion production and productivity. Conclusion: Therefore, farmers in both districts should use NPKSZnB compound fertilizer at these rates for optimum onion production.

PENGUJIAN KEAUSAN ALUMUNIUM MATRIX KOMPOSIT DIPERKUAT DENGAN KARBON NANOTUBE

Wear testing of engineering materials is an important aspect in evaluating their performance and durability. This study aims to investigate the wear-resistant ability of aluminum composites reinforced with carbon nanotubes (CNTs). The composite manufacturing process was carried out by infiltrating CNTs into the aluminum matrix through powder metallurgy method. Tests were conducted using two methods, namely pressing and sintering with temperature variations of 0oC (non sintering), 400oC, 500oC, 600oC and 700oC. The results showed that the specific wear value on the specimen obtained the best value at a sintering temperature of 400oC with a value of 0.003632850 mm3/kg.m and the highest value at a sintering temperature of 700oC with a value of 0.042771207 mm3/kg.m. And the wear rate on the specimen obtained the best value at a sintering temperature of 400oC with a value of 0.447887285 mm3/s and the highest value at a sintering temperature of 700oC with a value of 1.155387594 mm3/s. This shows that the addition of temperatures greater than 400oC has a major influence on the specific wear value and wear rate of sintering products. In addition, this method is also a reference for further researchers in developing aluminum carbon nanotube technology to obtain optimal results.

Understanding cellulose pyrolysis via ab initio deep learning potential field

Comprehensive and dynamic studies of cellulose pyrolysis reaction mechanisms are crucial in designing experiments and processes with enhanced safety, efficiency, and sustainability. The details of the pyrolysis mechanism are not readily available from experiments but can be better described via molecular dynamics (MD) simulations. However, the large size of cellulose molecules challenges accurate ab initio MD simulations, while existing reactive force field parameters lack precision. In this work, precise ab initio deep learning potentials field (DPLF) are developed and applied in MD simulations to facilitate the study of cellulose pyrolysis mechanisms. The formation mechanism and production rate of both valuable and greenhouse products from cellulose at temperatures larger than 1073 K are comprehensively described. This study underscores the critical role of advanced simulation techniques, particularly DLPF, in achieving efficient and accurate understanding of cellulose pyrolysis mechanisms, thus promoting wider industrial applications.

A Study of Fluctuation and Development Trend in Kharif Rice Cultivation in Odisha, India

It has been a concern in Odisha to see stable agricultural growth rates. Since rice is the main crop grown in the state, the current study's goals are to determine the district wise growth rate of area, production, and yield of kharif rice as well as to determine the degree of instability in those districts of Odisha. The study is based on secondary source of data on area, yield and production of kharif rice in the districts of Odisha from the period 1994-95 to 2017-18. The data are obtained from various volumes of Odisha Agriculture Statistics published by Directorate of Agriculture and Food Production, Government of Odisha. The growth rates for area, production and yield of kharif rice were computed for the districts of Odisha using exponential model. Cuddy Della Valle’s instability index was used to analyze the instability in area, production and yield of kharif rice in districts of Odisha. The compound growth rate in case of area was highest in Malkangiri and Subarnapur Districts. Lowest growth rate found in Kandhamal district. Compound growth rate for production are significant and highest in Subarnapur, Sundargarh, Jagatsinghpur and Boudh districts. Maximum districts showing positive growth rate in production and yield. Instability index for area of kharif rice in all districts of Odisha is insignificant except Bargarh and Jharsuguda which have significant Instability Index, which reveals that for the State, area is more stable as compared to that of yield and production. Despite stability of area, the instability of yield leads to instability of production.

Influencing Factors as well as Implementation Path of Synergistic Development of Digitalization and Greening in Manufacturing Industry: Analysis from a Configuration Perspective

&lt;p class="MsoNormal" style="text-align: justify;"&gt;&lt;span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;"&gt;The manufacturing sector must incorporate digitalization and greening as crucial strategies to attain high level of development in the context of the digital economy, given its significant role in quality of environment. Most of existing studies explore net effect of a single or several factors on the digitalization or greening in the manufacturing industry. Limited investigation has been done to integrate various factors impacting the connection and synchronized advancement of digitalization and greening within the manufacturing. Factors affecting the synergy of digitalization and green change within manufacturing are recognized in this article, and a theoretical framework is established to analyze. FsQCA tool is also put into use to survey configurational cases, which contains synergy degree of green digitalization from 30 provinces&amp;rsquo; manufacturing in China. Results show that: (1) Between 2007 and 2020, the development level of digital-green integration in the manufacturing industry shows an upward trend. There are three types of collaborative modes, namely, "industrial robot driven" "market development driven" and "market development driven - industrial robot driven", with each mode consisting of at least one to four equivalent pathways. (2) The marketization level and application of industrial robots are the important external and internal pulling forces that drive the synergy degree of digitalization and green change within manufacturing industry, respectively.(3) The influencing factors of the collaborative mode choice of digital-green development within manufacturing industry are complementary, among which, the degree of marketization is similar to the role of industrial robots in the configuration, which are capable to weaken the negative impact from insufficient government R&amp;amp;D investment support under specific conditions; (4) The non-high collaborative state of digital green in manufacturing industry is mainly due to the low level of marketization, openness, and economic development, as well as the low application rate of industrial robots and software products. This study enriches the theoretical understanding on digitalization and green change of manufacturing industry. Meanwhile, it also provides insights to advance the integrated and synergistic advancement of digital green transformation in manufacturing practice.&lt;/span&gt;&lt;/p&gt;

Robust Design of BLDC Motor Considering Driving Cycle

With growing environmental concerns and the limitations of fuel cell resources, replacing petrol-based engines with electric machines as the traction motor for electric vehicles (EVs) is gaining attention. Among the different electric machines topology, for lower power applications such as three-wheel motorcycle, the Brushless Direct Current (BLDC) motors are the most favorable due to their simple structure, simple control algorithm, etc. One of the key aspects of developing BLDC motors in EV applications is utilizing the fast and efficient optimization algorithm over driving cycles. Another aspect is considering manufacturing tolerances to eliminate the failure product rate in mass production. The combination of optimization algorithms with consideration of manufacturing tolerances leads to a complex and time-consuming optimization procedure. To overcome this problem, the robust design by utilizing the Design of Experiment (DOE) method can be utilized. In this study, first, a developed systematic multi-physics multi-level optimization algorithm with consideration of manufacturing tolerances and driving cycles is proposed. Then, to evaluate the accuracy of the optimization process, a prototype of the optimized motor is manufactured. The efficiency and accuracy of the optimization algorithm are compared through Finite Element Method (FEM) and experimental results, showing the effectiveness of the proposed algorithm.