Productivity In Manufacturing Industry Research Articles

Industry 4.0 and Sustainability: Analysis of Impacts and Proposed Guidelines

Objective: To survey the impacts of implementing new technologies with the Industry 4.0 concept in a large building materials and related products company and propose sustainable guidelines to minimize negative impacts. Theoretical Framework: Industry 4.0 technologies provide improvements in the product manufacturing process and industry performance through the use of data, but it is necessary to consider the integration of business with social, environmental and governance issues. Method: The methodological approach is a single case study, qualitative in nature, applied and exploratory in purpose. In developing the method, a list of impacts caused by the implementation of Industry 4.0 technologies was created from the theoretical framework, which gave rise to a questionnaire applied to the building materials and related products company by means of a field survey. Results and Discussion: 11 impacts were “observed” by the interviewee, 45 impacts, i.e. the majority of them, were classified as “not observed” and 10 impacts were considered to be “not applicable” to existing technologies due to the fact that the company is a retailer. After analyzing the impacts, sustainable guidelines were suggested for each negative impact. Research Implications: It can be concluded that in most of the literature searched, the economic pillar of sustainability was the most commonly found, thus highlighting the lack of analysis focused on environmental and social issues in the implementation of Industry 4.0 technology in the building materials industry. Originality/Value: It was observed that with regard to sustainability, the building materials and related products company has several very important practices, however, no studies applied to other companies were found in the scientific literature, a fact that makes the proposed work very important.

Is fair carbon mitigation practicable in China? Insights from digital technology innovation and carbon inequality

The uneven matching of distribution and targets in practicing carbon emission reduction has led to emission reduction inequality, while digital technology innovation (DTI) is expected to reduce these gaps. Therefore, this study casts new insights into modeling the nexus between DTI and carbon inequality using China's 286 prefecture-level cities from 2000 to 2021. Remarkably, city-level DTI performance is innovatively proxied by the related patent application volume, while the carbon inequality index within the region is measured using the environmental Gini coefficient. The main findings of this study include: (1) DTI robustly mitigates China's carbon inequality. (2) The effect of DTI is asymmetrically more significant in regions with a higher carbon inequality index. (3) DTI heterogeneously reduces carbon inequality more obviously in the eastern and central regions, and technology innovation in digital product manufacturing and digital technology application industries reduces carbon inequality more significantly. (4) More precisely, DTI strengthens carbon justice through income equalization, spatial agglomeration, and digital inclusion effects. Specifically, DTI significantly reduces income inequality and the digital economy's spatial agglomeration level and enhances digital financial inclusion, thereby reducing carbon inequality. This study also provides the policy implications for China.

The Effect of IoT Technology, Real-Time Analytics, and Digital Asset Management on Energy Efficiency and Productivity in Indonesia's Manufacturing Industry

This research investigates the impact of IoT (Internet of Things) technology, real-time analytics, and digital asset management on energy efficiency and productivity in the Indonesian manufacturing industry. A quantitative approach, employing structural equation modeling (SEM) with Partial Least Squares (PLS) 3 software, is utilized to analyze survey data collected from manufacturing firms across different sectors and sizes in Indonesia. The results reveal significant positive relationships between digital technologies (IoT, real-time analytics, digital asset management) and energy efficiency/productivity. Specifically, Digital Asset Management, IoT Technology, and Real-Time Analytics are found to have statistically significant effects on enhancing energy efficiency and productivity levels in Indonesian manufacturing operations. These findings underscore the transformative potential of digital technologies in driving operational performance and sustainability in the manufacturing sector. Policymakers, industry stakeholders, and practitioners can leverage these insights to inform strategic decision-making and investments in digital infrastructure, workforce development, and regulatory frameworks to foster innovation and competitiveness in the Indonesian manufacturing landscape.

Markov Method Revolutionizes Paper Industry, Slashing Maintenance Costs Globally

Paper manufacturing industries rely on efficient machinery for production processes, yet neglecting maintenance can lead to substantial costs. This study addresses the maintenance cost optimization challenge in a Pasuruan paper company, where maintenance expenses exceed 20% of the standard. Utilizing the Markov chain method, the research identifies optimal paper machine maintenance costs, achieving a 32% cost reduction. By analyzing data from company documents and literature reviews, specific machine states are identified, recommending overhaul strategies to enhance operational efficiency. The study's implications underscore the method's effectiveness in reducing costs and improving productivity for paper manufacturing industries, offering valuable insights for similar sectors. Highlights: 1. Neglecting maintenance in paper manufacturing leads to substantial costs.2. Markov chain method optimizes paper machine maintenance, reducing expenses.3. Implementation of optimal maintenance strategies significantly enhances financial sustainability. Keywords: Paper manufacturing, Maintenance optimization, Markov chain method, Cost reduction, Operational efficiency.

Low temperature phase transition mechanism of amorphous Al-oxalate to nano α-alumina

α-Alumina (α-Al2O3), widely used as a raw material or production in advanced manufacturing industry, has attracted much attention in terms of its preparation temperature. A simple dissolution-evaporation-precipitation process was employed to obtain the amorphous Al-oxalate (AAO) precursor, serving as the starting material for the low temperature preparation of nano α-Al2O3. The crystalline structure and thermal behavior of the AAO were compared with commercially available aluminum hydroxide (Al(OH)3) powder using the X-ray powder diffraction (XRD) instrument, the thermal gravity analysis and differential scanning calorimetry (TG-DSC). The phase transition mechanism of AAO was investigated by the fourier transform infrared spectroscopy (FTIR), transmission electron microscope (TEM), scanning electron microscope (SEM), and 27Al magic angle spinning nuclear magnetic resonance (27Al-MAS-NMR). The DSC results indicated that AAO underwent a phase transformation at 982 °C. The α-alumina diffraction peaks appeared in AAO at 1000 °C, while α-Al2O3 phase was observed for Al(OH)3 at 1200 °C. Furthermore, an absorption peak at 452 cm−1, corresponding to Al–O bond in α-alumina was detected at 1000 °C. The proposed low-temperature preparation mechanism of α-alumina from AAO is as follows: four coordination Al-oxalate species entities coexist within the AAO sample; with increasing temperature, organic acid functional groups oxidize and volatilize, resulting in the formation of tetra-coordinate [AlO4], penta-coordinate [AlO5], and hexa-coordinate [AlO6] atomic groups; these atomic clusters further polymerize to form a structurally dense α-alumina crystal at the nano-scale (∼50 nm) at around 1000 °C. The experimental findings present a novel approach and method for the low-temperature preparation of nano-sized alumina powder. Additionally, a feasible theoretical reference for the low-temperature phase transition mechanism of amorphous Al-oxalate was provided.

Turkey Paper and Paper Products Sector Import Forecasting with Artificial Neural Networks

The paper and paper products sector is a crucial component of the Turkish economy, characterized by significant interactions with various other sectors. Türkiye imports substantial amounts of paper, playing a vital role in the growth and sustainability of this sector. Accurate import forecasting is essential for strategic planning and resource management. This study aims to forecast the imports of the Turkish paper sector for the period from April 2023 to March 2024 using two artificial neural network (ANN) models: Multilayer Perceptron (MLP) and Radial Basis Function (RBF). The dataset, obtained from the Turkish Statistical Institute (TurkStat), covers 219 months of data from 2005 to 2023. The dependent variable is Türkiye’s monthly import value of paper and paper products, while the independent variables include the monthly average US Dollar exchange rate, monthly imports of Türkiye, the Manufacturing Industry Production Index, the Paper Production Index, and the monthly exports of paper and paper products from Türkiye. The MLP model forecasts that the monthly imports of paper and paper products will range between 270 to 300 million USD, while the RBF model predicts values between 268 and 321 million USD. These findings underscore the efficacy of ANNs in providing accurate and reliable forecasts. This study addresses a gap in the literature by applying ANN methods to forecast imports in the paper and paper products sector, presenting a novel approach that can assist companies in making better-informed decisions regarding inventory management, production planning, and marketing strategies. By leveraging the advanced computational power and pattern recognition capabilities of ANNs, the study aims to enhance the strategic planning processes in the paper and paper products industry. The traditional methods often used in trade data analysis and forecasting are limited in capturing the complex and non-linear relationships present in economic data. This study's application of ANNs offers a significant advancement by utilizing models that can better handle such complexities. The accuracy of the MLP and RBF models highlights their potential as valuable tools for economic forecasting, providing insights that are crucial for optimizing supply chain operations and improving market responsiveness. The results indicate that companies can achieve better operational performance and increased customer satisfaction by effectively forecasting future import requirements. The originality of this study lies in its methodological approach, utilizing ANN models to forecast import values in a sector where traditional methods have been predominant. This innovative approach not only contributes to the existing body of knowledge but also offers practical applications for businesses within the sector. The detailed analysis of the data, combined with the robust modeling techniques employed, provides a comprehensive framework for understanding the dynamics of paper imports and making strategic decisions based on accurate predictions. In conclusion, the study demonstrates the significant success of artificial neural networks in predicting import values for the Turkish paper and paper products sector. The findings provide valuable information that can aid companies in strategic planning, enhancing their ability to manage inventory, plan production, and develop effective market strategies. The research contributes to the literature by filling a gap with its innovative approach, offering new perspectives and practical applications for improving decision-making processes in the industry.

Localization of innovative technologies of industrial production as a tool for intensification of import substitution policy

The main criterion for the successful implementation of import substitution policy is the location of domestic production on the domestic territory of the state, in order to reduce the negative economic consequences of the industrial policies of unfriendly countries, with the orientation of domestic industrial enterprises towards their own intensification of production, including the production of analogous products to imported ones, for subsequent replacement of imported technologies with domestic ones and supply of domestic products to the domestic market – production and sale of own products. Localization of production is the placement of manufacturing or component industrial production facilities on its own, separate, local territory, in order to reduce the cost of products and bring them closer to assembly sites or sales markets. The term «localization of production», in the scientific literature, is represented by a special case of territorial organization (localized enterprises in separate territories) of production processes for the creation of material wealth, which has a number of features: in the organization of production, a company with a higher level of technological development forms the “conditions of the game”, organizing the distribution of production of certain products among all participants; localization is often carried out on the territory of another state, which has a lower level of development of technology and technology and a higher demand for final products in the markets of this state; An additional benefit of localization is the optimization of process logistics, bringing it closer to consumers. The goal of localization is to reduce production, transaction and logistics costs and increase the level of investment. The article presents the author's position on the development of intensification of the processes of industrial import substitution, in modern conditions, the main idea of which is the creation of localized production, a full technological cycle in the activities of Russian industrial enterprises, representing: at the initial stage, a full line of production of components and import substitution of missing parts, to meet demand in the domestic market, and in the future, the development of processes of substitution of imported technologies, the formation and use of advanced development technologies, increasing export potential and strengthening their presence of Russian industry in world markets. The work explores the essence of localization of production, which is determined by the production of parts and components manufactured in Russia, at national production facilities, using its own technologies, in order to increase the intensity of import substitution processes.

Design and fabrication of circular sheet metal shearing machine

The growing use of sheet metal in various industries such as automotive, packaging, medical appliances, cylinder production, Apparatus construction, Tank construction, Aircraft bodies, Missile production, Satellite dishes, road building and road signs, and household appliances, is attributed to its ease of manufacturing, handling, and use. To meet customer demands, sheet metal product manufacturing industries are working towards producing circular feature products of good quality at a large scale and low cost. To this end, this research emphasis the design, analysis, and fabrication of an electric circular sheet metal shearing machine, this would replace the punching and blanking operations and reduce scrap value from the stock material. The research includes concept design, detail design and analysis, assembly, 3D modelling, and fabrication of the Machine.

Assessment of opportunities for socio-economic sustainable development of small towns in Jambyl oblast

Achieving sustainable development of small towns as a special system is directly related, first of all, to maintaining socio-economic stability and creating a favourable environment for human life. Indeed, as a basis for the sustainability of small towns, the development of services, effective utilisation of local characteristics and diversification of socio-economic spheres are very important. Therefore, the purpose of this study is to assess the possibilities of socio-economic sustainable development of small towns in Zhambyl region. The study consisted of two stages: at the first stage a systematic analysis of statistical indicators of socio-economic development of Zhambyl region was conducted, the dynamics of sustainable development was assessed, at the second stage a survey was conducted and the information necessary for analysis was collected. The survey was conducted in the cities of Zhanatas, Karatau and Shu, which have the status of small towns in Zhambyl region. As a result of the survey, positive dynamics was noted for all indicators of socio-economic development of Zhambyl region. The volume of production in the region's manufacturing industry totalled 521.7 billion tenge, with a physical volume index of 111.1% compared to 2022. At the same time, the production of food products increased by 17.8%, chemical industry - by 5.5%, oil products - by 19.6%, finished metal products - by 31.9%, machine building - by 7.7%. However, according to the results of a survey conducted in the small towns of Zhanatas, Karatau and Shu, it became known that 31 per cent of respondents earn within 100-200 thousand tenge and 28 per cent within 60-100 thousand tenge. In addition, 66% of residents of small towns ask to increase the number of new jobs. Thus, the study revealed the need to modernise the socio-economic plan for sustainable development of small towns in Zhambyl region, the need to diversify the economy and improve the effective use of the environment.

A Bibliometric Review of Green Technology- Related Research in the Textile Industry

Despite being an impressive contributor to the world economy, traditional production and processing methods in the textile manufacturing industry cause significant waste and pollution. Green technology has emerged as a viable approach for mitigating environmental consequences. Numerous scholars have investigated green technologies; nonetheless, a more thorough analysis of the development and characteristics of green technology research in the textile industry is needed. This bibliometric study examined the growth patterns and trends of green technology research in the clothing industry from 2000 to 2023. The data were collected from the Scopus database, and the bibliometric analysis tool VOSviewer was used to visualise the data. The study results demonstrated the exponential growth trends of green textile technology research since 2020. The study also uncovered productive journals, countries, and institutions researching green textile technology. The results additionally showed that the United States (US), the United Kingdom (UK), and China exhibit substantial publications, and the UK is the leading country for collaborative research in green textile technology research. This study identified five primary research areas in the green textile technology literature: environmental impact assessment, life cycle assessment of textiles, sustainable design of textiles, sustainable fashion, and circular fashion supply chains. This analysis can assist academics in identifying novel research methodologies.

Multi-objective optimisation for energy saving and high efficiency production oriented multidirectional turning based on improved fireworks algorithm considering energy, efficiency and quality

To promote energy saving, high efficiency and quality production in mechanical manufacturing industry, a large number of studies have been conducted on parameters optimisation, especially for turning. However, most of the approaches have focused on single objective model and unidirectional turning (UDT). This paper presents a multi-objective parameter optimisation method for energy consumption, cutting time and surface roughness using new process of forward-and-reverse multidirectional turning (MDT). Firstly, the composition characteristics of cutting parameters for energy consumption, cutting time and surface roughness of MDT are analyzed to establish the corresponding models through nonlinear regression fitting, respectively. Then taking the minimum energy consumption, cutting time and surface roughness as the optimisation objectives, the improved fireworks algorithm can generate nearly 100 groups of optimal solutions. The most suitable processing parameters solution needs to be selected according to different machining requirements. In application scenarios, most relative errors of the models are within 10%. Comparing the machining performance of MDT and UDT under the same cutting parameters, the processing efficiency is increased by 25.97% and energy consumption is reduced by 12.38%, using the MDT. This study provides a multi-objective optimisation approach and models for MDT to reduce energy consumption, improve production efficiency and quality.

Energy efficient smart manufacturing of pharmaceutical solid oral dosage forms

Background: The global pharmaceuticals market is a trillion-dollar industry which grows more than 5% annually. However, in comparison to other manufacturing industries (e.g., oil refining, automotive), the pharmaceutical sector lags in manufacturing innovation and automation. In the production of pharmaceutical solid dosage forms, the use of energy utilization as a performance measure of production efficiency has neither been implemented extensively, nor been optimized to maximize efficiency. This study will focus on the development and implementation of a smart manufacturing platform to optimize energy productivity whilst maintaining tablet quality via the consideration of different manufacturing scenarios.
 Methods: This study will consider three main unit operations (wet granulation, drying and milling) which are relatively more energy intensive in pharmaceutical downstream processing, used to produce solid dosage forms, such as tablets. Four case-studies will be considered, which are 1: baseline batch, 2: baseline continuous, 3: optimized batch and 4: optimized continuous. Smart manufacturing is implemented to present optimized cases 3: and 4: Improvements in the energy and performance metrics are quantified and compared to the baseline cases. 
 Results and conclusions: The smart manufacturing platform used in this study, integrates advanced process model development, optimization, technoeconomic analysis and data integration. The utilization of this framework contributed to a ~70% and ~80% improvement in energy utilization in the optimized batch and continuous cases, respectively, when compared to the baseline batch case. In the optimized cases, tablet quality was maintained within targeted specifications and was comparable to the baseline batch case. This smart manufacturing framework can be generalized for drug product manufacturing and other particulate-based industries such as food, agriculture, and fine chemicals.

Recalculation of Manufacturing Industry Production Function with Trade Openness and Human Capital: Multi-Dimensional Panel Data Application

Recalculation of Manufacturing Industry Production Function with Trade Openness and Human Capital: Multi-Dimensional Panel Data Application

Effect of Wall Angle on Thickness Distribution in Single Point Incremental Forming: Finite Element Analysis and Theoretical Approach

The incremental sheet forming process (ISF) is the emerging forming process in the small size product manufacturing industries where as embossing, stamping, coining operations can be used to produce a product in large quantity. Therefore, ISF is one of the best solution to decrease the cost of production when a small quantity of product is demanded. In present study Efforts are devoted to study the effect of wall angle on sheet thinning, reaction forces, reaction moments, etc. for truncated cone of aluminium alloy (AA1050) using Finite Element simulation. Initially, A MATLAB code was written for spiral tool path. Modeling and simulation was done in ABAQUS software. Thereafter, a theoretical sheet thickness was computed using sine law and it was found out to be in close agreement with simulated sheet thickness.

Phycoremediation potential and agar yield of red macroalgae (Gracilaria corticata) against HEDP (hydroxyethylidene diphosphonic acid) and CAPB (cocoamidopropyl betaine) detergents and the heavy metal pollutants.

The discharge of raw industrial, agricultural, and domestic wastes leads to an increase in heavy metal (HM) burden and detergents in aquatic environs, which can have destructive effects on aquatic organisms. Agarophyte Gracilaria corticata, a major component of seaweed flora of the southern coast of Iran (Bushehr) that contains agar and red pigments, is one of the economically valuable red marine algae. Agar is one of the important polysaccharides with high economic value, widely used in pharmaceutical, medicinal, and cosmetic product manufacturing industries. The aim of this work was to investigate the effect of 5 HMs and two common surfactants in household and industrial detergents on the agar yield, appearance color, and the red algae's phycoremediation potential against HMs. The metal ions were Zn(II), Cu(II), Ni(II), Mn(II), and Cr(VI), and the surfactants were HEDP and CAPB. The analysis results of samples cultured for 60 days in seawater and polluted environments showed that G. corticata can accumulate copper and nickel. In the presence of detergents without HMs, the amount of extracted agar significantly increased compared to the control sample with no change in algae color. But with increasing concentration of HMs, the amount of agar in seaweed samples decreased significantly, and the algae discolored from red to dark green or yellowish-green color (signs of death in the algae). These results show that increasing of HM pollution and detergents can lead to toxicological effects and reduce the species diversity of red seaweeds in the future.

The dynamic impact of digital economy on the green development of traditional manufacturing industry: Evidence from China

The traditional manufacturing industry is China’s second-largest source of carbon emissions, and the successful completion of dual carbon target depend on the traditional manufacturing industry’s ability to reduce emissions. This paper constructs the evaluation index system to analyze the driving factors and green coupling level of the digital economy enabling the green development of traditional manufacturing industry from three aspects: industry digitalization capacity, socio-economic benefits capacity and ecological resources carrying capacity based on the theory of social shaping of technology. From the perspective of regional economic development, this paper constructs the spatial Durbin model and threshold regression model to analyze the mediation effect and spatial spillover mechanism of the digital economy empowering the green development of traditional manufacturing industry. Based on the panel data of 30 provinces in China from 2012 to 2020, the empirical analysis show that digital economy has the positive impact on the green development of traditional manufacturing industry through the digital innovation, industrial upgrading and human capital. At same time, the digital economy has a positive spatial autocorrelation pattern of the green development of traditional manufacturing industries with “high in the eastern and low in the western of China” from the global Moran index. Through the policy test of carbon-trading pilot programs by the difference-in-differences model, the digital economy has a non-linear impact on the intensive production of traditional manufacturing industry, which green finance activate the new impetus of market and the data element resources enhance industrial coordination development.

Biodegradable Packaging Materials for Foods Preservation: Sources, Advantages, Limitations, and Future Perspectives

Biodegradable packaging materials generally comprise a solution to the environmental problem caused by the consecutive use of conventional packaging materials (petroleum-based materials) even though these have a high cost. The monomers resulting from the slow degradation of petroleum-based materials contribute to the pollution of the environment. Biodegradable packaging materials distinguished by high biodegradability and biocompatibility can successfully replace the aforementioned packaging materials and thus solve the environmental problems caused by their use or deposition. Although several of the biodegradable packaging materials present defective properties, mainly mechanical and barrier properties, these are reduced or even eliminated by the addition of various improving additives and by blending them with other biopolymers. Various natural preservatives such as essential oils or other phytochemical extracts can also be incorporated into the biopolymer network to increase its efficacy. This treatment is particularly beneficial since it contributes to the increasing of the shelf life and storability of packaged foods such as fruits, vegetables, dairy products, meat and its products, poultry, and fish. For all the above reasons, the preferences of consumers and the critical thinking/decisions of the food product manufacturing industries in favor of the potential use of biodegradable packaging materials in foods are increasing more and more. In this context, the present review article addresses the most recently used biodegradable packaging materials for foods preservation by presenting their sources, advantages, limitations, and future perspectives.

Features of the development of the wood processing industry under the conditions of the marital state

The article analyzes the peculiarities of the development of the woodworking industry in the conditions of martial law, and on the basis of the studied material, the factors and aspects of the influence of the legal regime of martial law on the development of the industry are given. It was analyzed that the realization of woodworking products in the period from 2010 to 2021 was estimated on the basis of the dynamics of production, which includes paper and printing activities, which, according to the analysis, amounted to about 6% of the total volume of realization of manufacturing industry products. In 2021, 5.35% of the completed work was spent on the purchase of the most valuable woodworking skill. It was determined that the development of the woodworking industry under martial law requires flexibility, innovation and the ability to adapt to changing conditions. At the same time, it can perform an important function in meeting the needs of the military complex and contribute to economic recovery after the end of the conflict. Aspects that may affect the woodworking industry during martial law are suggested, including: reduced production, dependence on imports, diversion of resources, aspects related to destruction, restrictions on exports and trade, etc.

Fake Product Detection Using Blockchain Technology

Abstract: There are several fake products in the existing supply chain markets. It is necessary to have a system for end users to check all details about the product they are buying so that the customer can check if the product is genuine. In recent years, faking products play an important role in product manufacturing industries. Faking products affects the company name, sales, and profit of the organizations. Blockchain technology is used for the identification of actual merchandise and the detecting of faux products. Blockchain technology is generally a tally system that stores all the data of the deals that take place in it. The precise aspect approximately this era is that the tally we referred to is a allotted tally in a peer-to- peer community. Blockchain generation is relaxed as the facts saved once within the chain is immutable consequently any block cannot be modified or hacked. with the aid of using Blockchain era, clients or customers do no longer want to rely on users for confirmation of product authenticity and protection. Our device affords the rising generation of web use instances, and brief reaction (QR) codes offer a unique but affectable method to triumph over these faking of products. Counterfeited merchandise may be detected the use of a QR code scanner, wherein the QR code of the product is linked to the Blockchain. So, this system can be used to store product info and generate particular code of that product as blocks inside the database. It collects the precise code from the consumer and compares the code against entities within the Blockchain database. If the code matches, it will give all the information about the product otherwise no data can be outputted to the purchaser which shows that the product is fake or counterfeited.

Research on multi-objective collaborative control of complex product development in equipment manufacturing industry

Abstract Equipment manufacturing involves the integration of multiple technologies and is a complex product system. In the independent innovation of complex product systems, product development is the most important way. Multi-objective cooperative control has been applied to various industries with remarkable results. In this paper, high quality research and development of complex products in equipment manufacturing industry is the main goal. Inspired by the dimensional parameters of the key structures of the product and the structure of the endocrine regulation network, a multi-objective collaborative controller consisting of a speed and position coordinator, a module consisting of a speed and position coordinator, a hormone discriminator, a hormone optimizer, and a controller is designed. The data from the cooperative control study shows that when the controller parameters [3, 1, 2] are used, the velocity parameter is 0.7, the differential parameter is 0.04, and the controller output parameter is 0.8. The force control parameter is 2, the differential parameter is 0.05, and the controller output parameter is 0.7. In the multi-objective cooperative control experiment, the navigator makes a uniform circular or uniform linear motion with [v 1, w 1] T = [0.06,0.09] T . The vector forms r 2 d = [0.4,0.4] T, r 3 d =[−0.1,0.2] T ,. Both the red curve and the blue curve of the follower appear jittered. The experimental curves and control trajectories illustrate that the controller has good control over the vibration and shock phenomena that occur during the position and speed as well as force control of the product. And exhibits good tracking performance. It shows that the multi-objective collaborative controller plays a role in improving the quality of the development of complex products in the equipment manufacturing industry.