Product Process Research Articles

Social life cycle assessment of garments production using the psychosocial risk factors impact pathway

This study presents the application of a Social Life Cycle Assessment (SLCA) methodology to two Italian case studies, allowing to estimate the possible impacts of the production of two garments “A” and “B”. The hours of exposure to health risks have been accounted for the workers since they are the stakeholder group most immediately impacted. They have been analysed through the Psychosocial Risk Factors (PRF) impact pathway, a type II Social Life Cycle Assessment that allows the quantification of hours of exposure per each phase of the product or service life cycle. Using questionnaire, technical data have been gathered and all productive phases quantified and qualified in terms of duration (hours) and working conditions (ergonomics, exposures, postures, etc.). A literature review has been conducted to find relationships between these working conditions with health problems through odds ratios, a statistical measure of association between variables commonly used in retrospective studies. The functional unit chosen is one garment, and the system boundary is from cradle to firm gate; however, due to the lack of specific information concerning the upstream processes, impacts about inputs supplied from external providers were only qualified, but not quantified (background data). In both case studies, the highest psychosocial risk is linked to musculoskeletal disorders (Low back pain and neck and shoulder pain) and visual fatigue and discomfort. These results are due principally to the postures needed during work, the concentration required, repetitive movements, static and dynamic loads, as well as the use of video monitors during some tasks (especially planning and CAD modelling). Apparently, the process of product “B” is more socially impacting than “A”. Actually, this is due because of the internalization of some operations such as (part of) the fabric production and the dyeing processes, which can expose workers to hazardous chemicals and dusts, and the use of trichloroethylene for stain removal. These working conditions, indeed, expose workers to a higher risk of cancers, according to scientific literature. To reduce risks, it is suggested to avoid the use of bleach and trichloroethylene for cleaning, to reduce the exposure to textile dusts (for example with the use of vacuums or masks), to avoid skin contact with the azo dyes and azo pigments, by using protective individual dispositive such as gloves, long-sleeved shirts, and aprons. To improve the ergonomics workplace, it is recommended to take more breaks during the timework, ensure the firmness of chairs and add lumbar support, as well as control the height of chairs and worktops. Promoting employees’ physical activity would be useful to prevent musculoskeletal disorders.

Innovative culture and differences for product versus process innovation: reflect on Confucianism and Taoism

ABSTRACT This article examines the difference between innovative culture for product innovation vs. process innovation and sheds light on Confucian and Taoist philosophical roots in innovative cultures for the two types of innovation. We first identify four dimensions of innovative culture: freedom, openness, team spirit, and support & career development, and hypothesise that freedom and openness are more emphasized in innovative culture for product innovation, while team spirit and support & career development are more stressed in innovative culture for process innovation. Using survey data from 33 high-tech enterprises in China, we find support for our predictions. We further analyse that Taoism is more relevant to innovative culture for product innovation, whereas Confucianism is more related to innovative culture for process innovation. By distinguishing innovative cultures between product vs. process innovation and relating to Confucianism and Taoism, this paper provides a nuanced as well as philosophical understanding of innovative culture.

Assessing the effect of COVID 19 lockdowns on the composition of organic compounds and potential source of PM2.5 in Hanoi, Vietnam.

The ambient air quality during COVID-19 lockdowns has been improved in many cities in the world. This study is to assess the changes in persistent organic pollutants in PM2.5 during the COVID-19 lockdown in Hanoi. Individual organic species in PM2.5 ((e.g., polycyclic aromatic hydrocarbons (PAHs), polychlorobiphenyls (PCBs), and organochlorine pesticides (OCPs)) were measured in an urban residential area in Hanoi from before the March 10th to April 22nd, 2020, including before the partial lockdown (BL) and the partial lockdown (PL) phases. During the PL phase, the concentration of Σ14PAHs and Σ28PCBs was reduced by 38 and 52% compared with the BL period, respectively. The diagnostic ratio method implied that the sources of PAHs within the PL phase had a less effect on traffic and industrial activities than in the BL phase. The characteristic ratio method indicated that PCBs were mixed by commercial product and combustion process in both the BL and the PL periods, however, the source of PCBs in the BL phase was influenced by municipal waste incineration more than those in the PL phase. The decreasing concentration of Σ20OCPs during the partial lockdown was attributed to the restriction of human activities during the quarantine period. The results suggested that the source of OCPs was probably derived from the usage of pesticides in current and, historical degradation or the transportation of pesticides from the soil to the atmosphere.

Myofibrillar protein hydrolysis under hydroxyl radical oxidative stress: Structural changes and their impacts on binding to selected aldehydes

In this study, a hydroxyl radical oxidation system was established to simulate the oxidation process in fermented meat products. This system was employed to examine the structural changes in myofibrillar proteins (MPs) resulting from tryptic hydrolysis after a hydroxyl radical oxidative regime. The effect of these changes on the ability of MPs to bind selected aldehydes (3-methyl butanal, pentanal, hexanal, and heptanal) was also investigated. Moderate oxidation (H2O2 ≤ 1.0 mM) unfolded the structure of MPs, facilitating trypsin-mediated hydrolysis and increasing their binding capacity for the four selected aldehydes. However, excessive oxidation (H2O2 ≥ 2.5 mM) led to cross-linking and aggregation of MPs, inhibiting trypsin-mediated hydrolysis. The oxidised MPs had the best binding capacity for heptanal. The interaction of the oxidised trypsin-hydrolysed MPs with heptanal was driven by hydrophobic interactions. The binding of heptanal affected the structure of the oxidised trypsin-hydrolysed MPs and reduced their α-helix content.

Quality and safety of new types of dairy products based on cow’s and mare’s milk with vegetable additives

The modern market of dairy products is quite developed, but the issue of compliance with the quality and safety of their production remains relevant. The purpose of this paper was to study the organoleptic, physicochemical and safety indicators of combined dairy products based on mare’s and cow’s milk using herbal supplements. In the course of the research, analytical and statistical methods of information processing were used; experimental studies of raw materials and the finished combined product, namely the determination of acidity, solids, fat and protein; energy and biological values of the product were calculated. Technological processes of combined dairy products based on cow’s and mare’s milk using a vegetable origin filler were studied. Of the three prototypes of the proposed dairy products, it was determined to recommend samples No. 2 and 3. High quality indicators are observed in them, in particular, a rich taste with a pronounced taste of additional components, a pleasant smell and appearance. Also, the finished product in samples No. 2 and 3 have high safety indicators. Pathogenic and harmful microorganisms and substances were not found, acceptable microorganisms are within the maximum permissible limits. According to the research results, new dairy products are recommended using vegetable raw materials with different fat, protein, energy value, caloric content and lactose content. In the process of writing this paper, indicators of nutritional, energy value and safety of new types of dairy products based on cow and mare’s milk with vegetable additives were determined. Taking into account the research results and the materials of previous scientific papers, authors consider it promising to develop and sell dairy products based on cow’s and mare’s milk using a filler of plant origin. The advantages of the resulting product include: consumer interest in such products, high quality indicators, product safety, the possibility of using products in functional and specialized nutrition.Graphical

MAXIMIZING INNOVATION: ANALYZING THE INFLUENCE OF TECHNOLOGY PARTNERSHIP PORTFOLIOS ON FIRM PERFORMANCE

Innovation is a cornerstone of competitive advantage in today's dynamic business environment, and firms often collaborate with external partners to enhance their innovation capabilities. This study examines the influence of technology partnership portfolios on firm innovation performance. Drawing on data from a diverse sample of firms across industries, we analyze the composition and dynamics of technology partnership portfolios and their impact on various dimensions of innovation performance, including product innovation, process innovation, and overall firm competitiveness. Our findings shed light on the strategic importance of managing technology partnerships effectively to maximize innovation outcomes and sustain long-term competitive advantage.

Study on the treatment of pyrolysis products from the nitric acid pressure leach liquor of laterite

As the demand for nickel increases sharply, it is of great significance to extract valuable metals such as nickel and cobalt from lateritic nickel ore with huge reserves. Based on the nitric acid pressure leaching process (NAPL) of laterite nickel ore, a clean process of laterite nickel ore treatment is proposed. The process includes concentration and crystallization of pressure leaching solution of nitric acid, pyrolysis of mixed nitrate crystal, alkaline leaching of mixed oxides and acid leaching of alkaline leaching residue. Based on previous work, the high-pressure alkaline leaching process of pyrolysis products (mixed oxides) and atmospheric pressure sulfuric acid leaching process of alkaline leaching residue were studied in this paper. First, the Eh-pH diagrams of metal-water system of common elements in laterite nickel ore was summarized according to the reaction equations of different substances in aqueous solution, and the subsequent wet leaching process was guided. The following alkaline leaching experiments showed that under the conditions of 300 g/L NaOH concentration, 3.5 mL/g liquid–solid ratio, 160 °C leaching temperature and 1 h leaching temperature, 85.0 % of aluminum in mixed oxides can be leached and scandium can be enriched by 13 times. Finally, under the conditions of initial sulfuric acid concentration of 4 M, temperature of 100 °C, leaching time of 30 min and liquid–solid ratio of 4 mL/g, the leaching rates of Al, Ni, Mg, Co, Mn, Fe and Sc in alkaline leaching residue were 92.0 %, 97.5 %, 98.4 %, 92.3 %, 62.7 % and 68, respectively. A new procedure for treating lateritic nickel ore is proposed, allowing for thorough recovery and usage of important components. The technique is green and environmentally benign, resulting in closed-loop production of laterite-nickel ore treatment with numerous application possibilities.

A STUDY ON IMPROVING SUPPLY CHAIN USING BUSINESS INTELLIGENCE CONCERNING DHARA LOGISTICS

Business intelligence (BI) is software that ingests business data and presents it in user-friendly views such as reports, dashboards, charts and graphs. BI tools enable business users to access different types of data — historical and current, third-party and in-house, as well as semi-structured data and unstructured data like social media. Users can analyze this information to gain insights into how the business is performing. According to CIO magazine: “Although business intelligence does not tell business users what to do or what will happen if they take a certain course, neither is BI only about generating reports. Rather, BI offers a way for people to examine data to understand trends and derive insights.” Organizations can use the insights gained from business intelligence and data analysis to improve business decisions, identify problems or issues, spot market trends, and find new revenue or business opportunities. BI platforms traditionally rely on data warehouses for their baseline information. A data warehouse aggregates data from multiple data sources into one central system to support business analytics and reporting. Business intelligence software queries the warehouse and presents the results to the user in the form of reports, charts and maps. Data warehouses can include an online analytical processing (OLAP) engine to support multidimensional queries. “OLAP provides powerful technology for data discovery, facilitating business intelligence, complex analytic calculations and predictive analytics,” says IBM offering manager Doug Dailey in his data warehousing blog. “One of the main benefits of OLAP is the consistency of information and calculations it uses to drive data to improve product quality, customer interactions and process improvements.” Some newer business intelligence solutions can extract and ingest raw data directly using technology such as Hadoop, but data warehouses are still the data source of choice in many cases.

Increasing Production Capacity through Halal Product Process Assistance to SMEs in Bajeng District, South Sulawesi

Increasing Production Capacity through Halal Product Process Assistance to SMEs in Bajeng District, South Sulawesi

Identification of propagation path and root cause of faults based on generative adversarial networks in industrial systems

Fault diagnosis and detection (FDD) improves product quality, process safety, and profitability in modern industrial plants. Faults can propagate between different parts of plants due to connections between devices and control loops. As a result, control room operators may receive multiple alarms that distract their attention from addressing the main causes of abnormal situations. Therefore, investigating causal relationships between process variables is essential in determining the root cause of faults. This study proposes a new systematic approach for causality analysis to identify the propagation path and root cause of faults in industrial plants. The research's innovations are categorized into two main parts. Initially, the study utilizes machine learning algorithms to identify causal relationships using probabilistic concepts. Additionally, it introduces a novel architecture by merging the generative adversarial network (GAN) with the variational auto-encoder (VAE). The process variables are mapped to a latent space, where an adversarial generative network will investigate the causal relationship between variables. Finally, the Tennessee Eastman Process simulation and gas turbine industrial data are used to evaluate the proposed algorithm.

Accelerating Process Development and Product Formulation.

Currently, the lengthy time needed to bring new drugs to market or to implement postapproval changes causes multiple problems, such as delaying patients access to new lifesaving or life-enhancing medications and slowing the response to emergencies that require new treatments. However, new technologies are available that can help solve these problems. The January 2023 NIPTE pathfinding workshop on accelerating drug product development and approval included a session in which participants considered the current state of product formulation and process development, barriers to acceleration of the development timeline, and opportunities for overcoming these barriers using new technologies. The authors participated in this workshop, and in this article have shared their perspective of some of the ways forward, including advanced manufacturing techniques and adaptive development. In addition, there is a need for paradigm shifts in regulatory processes, increased pre-competitive collaboration, and a shared strategy among regulators, industry, and academia.

乡村振兴战略下农产品跨境电商赋能乡村特色产业的研究

China is an agriculture-based country with vast rural areas, a wealth of agricultural products, and a large market. Cross-border e-commerce offers support for the export of agricultural products, which can break through the limitations of time and space, shorten the trade process of agricultural products, enhance the export efficiency of agricultural products, stabilize agricultural product trade, and promote the transformation and upgrading of China’s e-commerce. It also aids in the construction of a long-term mechanism for e-commerce poverty alleviation and agricultural revitalization. However, research has found that despite the rapid development of China’s crossborder e-commerce for agricultural products, there are still some issues, such as non-uniform quality standards for export agricultural products, information asymmetry, an inadequate cross-national logistics system and level of logistics technology, low levels of after-sales service, and a lack of corresponding professional and technical personnel. To address these issues, this article first introduces the current situation of China’s agricultural product export via cross-border e-commerce, then analyzes the development opportunities, and finally proposes the following solutions: aligning with international standards by establishing strict quality control mechanisms; creating a favorable policy environment, including policy support, resource allocation, and organizational guarantees; continuously improving product quality; focusing on the training of professional talent; and strengthening quality supervision and risk prevention. The aim is to promote the development of cross-border ecommerce for agricultural products, empower rural specialty industries, and support the implementation of the rural revitalization strategy.

Evaluation of factors affecting the freeze-dried process of durian (Durio zibethinus L.)

Durian (Durio zibethinus L.) is a famous fruit with high economic values in Vietnam and is gradually becoming popular worldwide. However, studies have shown that durian flesh can quickly deteriorate after 3-4 days of storage at room temperature. Besides developing suitable preservation methods, research on diversifying durian products is a sustainable solution that should be considered. The objective of this research is to develop a freezedrying process for durian-based products with good organoleptic quality as well as high nutritional value. Several factors were selected for the present study, including durian flesh thickness (1, 2 and 3 cm), freezing time (180 mins, 360 mins, 540 mins and 660 mins), and drying time (360 mins, 600 mins and 840 mins). The experiments were carried out in a one-factor arrangement. Results have shown that all surveyed factors have a statistically significant influence on moisture, hardness, color difference, and total polyphenol content (p<0.05). The best drying efficiency was obtained when durian flesh thickness was 1 cm, freezing time of 540 min and drying time of 600 min. Samples after drying have moisture 2.87%, hardness 20.76 N/cm2 , total polyphenol content 107.02 mg GAE/100 g dry material and no fat oxidation (as evidenced by peroxide index). This research result was considered basic data for the application of freeze-dried durian products on an industrial scale in the future.

Analysis of interplay between food safety systems and halal standards in Indonesia

The present work aimed to develop a comprehensive certification process for halal food products within the Indonesian agribusiness, which integrates food safety and halal standards. The objective was to reduce financial barriers, certification burden, and workforce shortages currently impeding the establishment of quality halal food supply chains. To achieve this aim, Interpretive Structural Modelling (ISM) was used to elucidate the complex relationships between decision variables in the halal certification process. Data collection included interviews with sectoral experts overseeing food safety and halal compliance. The present work identified 17 strategic variables crucial to integrating the Halal Assurance System (HAS) with food safety using ISM analysis. The findings of the ISM model showed 11 hierarchical levels of integration between the HAS and food safety, identifying key factors influencing produce security mechanisms. Additionally, the present work emphasised the significance of transparency, proper handling of produce, and efficient certification processes for businesses operating in the global food sector. This proposed framework not only offers practical guidance for enhancing food security, but also correlated certification processes with supply chain objectives, thereby bridging the gap between theory and practice.

Product Quality Anomaly Recognition and Diagnosis Based on DRSN-SVM-SHAP

Conventional quality control methodologies are inadequate for fully elucidating the aberrant patterns of product quality. A multitude of factors influence product quality, yet the limited number of controlled quality characteristics is insufficient for accurately diagnosing quality abnormalities. Additionally, there are asymmetries in data collection, data pre-processing, and model interpretation. In this context, a quality anomaly recognition and diagnosis model for the complex product manufacturing process is constructed based on a deep residual network, support vector machine (SVM), and Shapley additive explanation (SHAP). Given the numerous complex product quality characteristic indexes and unpredictable accidental factors in the production process, it is necessary to mine the deep relationship between quality characteristic data and quality state. This mining is achieved by utilizing the strong feature extraction ability of the deep residual shrinkage network (DRSN) through self-learning. The symmetry of the data within the model has also been taken into account to ensure a more balanced and comprehensive analysis. The excellent binary classification ability of the support vector machine is combined with the DRSN to identify the quality anomaly state. The SHAP interpretable model is employed to diagnose the quality anomaly problem of a single product and to identify and diagnose quality anomalies in the manufacturing process of complex products. The effectiveness of the model is validated through case analysis. The accuracy of the DRSN-SVM quality anomaly recognition model reaches 99%, as demonstrated by example analysis, and the model exhibits faster convergence and significantly higher accuracy compared with the naive Bayesian model classification and support vector machine classification models.

A patent retrieval method and system based on double classification

As one of the most prominent carriers of knowledge, patents can provide masses of cross-domain knowledge to support the innovative design process of products. However, there is a major problem faced by most patent-aided innovation design systems, that is, identifying and providing patents related to design requirements from a multitude of cross-domain patents. To address this problem, a patent retrieval method based on double classification is proposed in this study, and a corresponding patent-aided innovative design prototype system is also developed. Firstly, the functional attributes are extracted from design requirements and expanded to different fields based on functional bases, by which the primary patent sets are constructed via classifying cross-domain patents. Secondly, technical features are mined from the primary patent sets with the topic model, which is used to classify the primary patent sets in turn and construct the secondary patent sets, hence, corresponding patents can be obtained to solve the design problems. Finally, a patent-aided prototype system is developed based on the proposed method. On the basis of the system, the hole plug of irradiated samples of nuclear reactor pressure vessel has undergone innovative design, which verifies the feasibility and practicability of both the method and system.

Barriers to Older Adults Adapting Smart Homes: Perceived Risk Scale Development

The 21st century has marked the dawn of an aging population. China’s aging process ranks first worldwide. The country has recognized the gravity of this demographic shift and implemented strategies to address it at the national level. A vast majority of elderly Chinese individuals (approximately 90%) aspire to age in their own homes. Smart homes, endowed with cutting-edge digital technologies, such as AI, the Internet of Things, and big data, hold vast potential for enabling this vision. However, acceptance of smart home products and services among elderly individuals in China remains low. The main reason is that the related products and services fail to effectively alleviate the perceived risk of this population in the R&D process of related products and services, and there is a lack of effective measurement methods. To holistically assess the potential obstacles faced by elderly individuals using smart home products and services, this study targeted individuals aged 45–60 years in China. This study aimed to develop a comprehensive perceived risk scale specific to smart homes for this demographic. Initially, this study identified key risk dimensions and corresponding measurement items through a rigorous literature review, user interviews, and expert consultations. Subsequently, it ensured the reliability and validity of each dimension and its corresponding observation variables through preliminary research, exploratory factor analysis, and confirmatory factor analysis. This approach allowed for a comprehensive understanding of the challenges faced by future elderly individuals when utilizing smart home products and services, thus enabling the development of more effective solutions. The scale encompassed ten factors and seventy measurement items, including Privacy and Security Risk (seven items), Physical Risk (seven items), Technological Risk (nine items), Performance Risk (seven items), Service Risk (nine items), Financial Risk (five items), Psychological Risk (seven items), Industry and Market Risk (six items), Social Support Risk (six items), and Policy and Legal risk (seven items). The measurement scale developed in this study represents a groundbreaking first attempt to create a systematic scale for assessing the perceived risks associated with smart homes for the elderly in China. It not only enables professionals, businesses, and manufacturers to avoid or reduce barriers in the R&D process of related products and services, facilitating smart home industry growth and enhancing user adoption, but also serves as a universal reference for the potential obstacles that digital technology may encounter in addressing aging-related issues, which has significant theoretical value and practical importance.

An approach to coupling analysis for open architecture product

During the configuration process of open architecture products (OAPs), adaptive change is inevitable to meet customers' personalised demands. However, the coupling between modules makes adaptive changes of open architecture products more difficult. For the coupling between modules in open architecture product design, an approach to analysing the coupling between modules is proposed. The implications of adaptive change for open architecture products are explained, and the interface relationships among the common platform, customised modules, and personalised modules are analysed. The coupling modes of three cases are discussed, i.e. the coupling between modules under the same branch, between modules under different branches with only functional collaboration, and between modules under different branches with function-structure correlation. The coupling degrees are calculated with consideration of the number of connections between modules and their comprehensive correlation degree. The structural complexity of the module is considered by development cost, development time, change cost, and change time, which is expressed with the information content in axiomatic design. Based on structural complexity, the dependency, and coupling degree between modules, the calculation method of change impact degree between modules is presented. The method on coupling analysis between modules in open architecture product design for personalised electric winches is illustrated.

Investigation into the Impact of Groove Shape on the Tensile Strength of Commercial Steel

In the industrial landscape, welding holds a prominent position, with a significant demand for both effective and high-quality welding processes. Manufacturers, striving to maintain competitiveness, rely on their manufacturing engineers and production personnel to swiftly and efficiently establish manufacturing processes for new products. Among the various welding methods employed, Gas Metal Arc Welding (GMAW) stands out as one of the most widely utilized processes. Several input factors, including welding current, welding voltage, gas flow rate, wire feed speed (WFS), wire size, and welding speed, play a crucial role in determining the quality of welding outcomes. Taguchi's design, recognized for its effectiveness, serves as a powerful optimization tool for enhancing the quality and performance output of manufacturing processes. In this particular study, GMAW was employed to weld commercial steel under predetermined factors of welding voltage, WFS, and groove shape. The X-groove welding exhibited lower tensile strength and hardness compared to V-groove weldments. Utilizing Taguchi's design, the objective was to identify the optimal process factors that would result in higher tensile strength and hardness. The analysis revealed that welding groove shape had the most significant impact on both tensile strength and hardness, followed by voltage. In contrast, WFS exerted the least influence on tensile strength and hardness. The optimized combination of welding factors identified was a V-groove shape, 20 V welding voltage, and a 5.9 m/min WFS.

ANALYSIS OF THE MARKETING MIX STRATEGY (7P) TO INCREASE SALES OF PROCESSED CASSAVA PRODUCTS AT UD "PURNAMA JATI" MEMBER

One of the leading producers and exporters of cassava in the world is Indonesia. Jember Regency is one of the highest cassava production centers in East Java, with an annual production capacity of 9,492 tons. This processed tape food product, typical of Jember Regency, is produced from the high supply of cassava. There is a need to find processed cassava products considering the high interest in tape products because of their unique quality, so this product is much more popular as souvenirs or souvenirs typical of Jember. The research aims to perfect marketing tactics and determine how the marketing mix (7P) influences consumer decisions in purchasing processed cassava products from UD Purnama Jati Jember. Questionnaire methodology is a technique for collecting information through statements or questions asked to respondents. Because the p-value is smaller than 0.05, product, price, place, and employees influence the results of consumer purchasing decisions at UD Purnama Jati. However, because the p-value is more significant than 0.05, we can rule out the possibility that factors related to the product process, physical evidence, or advertising influence consumers' final purchasing decisions