Assembly Line Production Research Articles

Vaccine production optimization model based on Monte Carlo algorithm

COVID-19 is ravaging the world. Due to the large scale of vaccine production, the production of vaccines with good quality and quantity is the key to epidemic prevention and control. The problem of vaccine production planning is essentially the same as the problem of assembly line production. Based on the production sequence of a company's vaccine, this paper conducted a normal test on the test data by USING SPSS software and found that it obeys the normal distribution. The shortest processing time and production sequence were obtained by using LINGO software. By using LINGO software, it was found that the processing time was the shortest, 184.778 minutes, in the order of YM4 -- YM5 -- YM10 -- YM7 -- YM8 -- YM1 -- YM2 -- YM3 -- YM9 -- YM6. Based on the above conclusion, monte Carlo experiment was conducted with MATLAB software to find out the maximum probability corresponding to 95% of the production time in the problem, and the result was 1.324%. To mean the lower limit of the 90% confidence interval of each flight reservation production time for each type of vaccine, ignore the machine production of waiting time and each vaccine production after the influence on other types of vaccine production, statistics each vaccine needed to consume the longest flight reservation, the total elapsed time, again will each vaccine consume the longest flight reservation of accumulative sum total production time, The number of production days is 186.189 days under the premise that the reliability is 90%.

Wire Harness Assembly Process Supported by Collaborative Robots: Literature Review and Call for R&D

The wire harness assembly process is a complicated manufacturing activity, which is becoming more complex because of the evolving nature of mechatronic and electronic products that require more connectors, sensors, controllers, communication networking, etc. Furthermore, the demand for wire harnesses continues to grow in all industries worldwide as the majority of equipment, appliances, machinery, vehicles, etc., are becoming “smart” (i.e., more mechatronic or electronic). Moreover, most of the wire harness assembly process tasks are done manually, and most of these are considered non-ergonomic for human assembly workers. Hence, the wire harness manufacturing industry is faced with the challenge of increasing productivity while improving the occupational health of its human assembly workers. The purpose of this paper is to conduct a literature review exploring the state of the use of collaborative robots in the wire harness assembly process due to their potential to reduce current occupational health problems for human assembly workers and increase the throughput of wire harness assembly lines, and to provide main findings, discussion, and further research directions for collaborative robotics in this application domain. Eleven papers were found in the scientific literature. All papers demonstrated the potential of collaborative robots to improve the productivity of wire harness assembly lines, and two of these in particular on the ergonomics of the wire harness assembly process. None of the papers reviewed presented a cost–benefit or a cycle time analysis to qualitatively and/or quantitatively measure the impact of the incorporation of collaborative robots in the wire harness assembly process. This represents an important area of opportunity for research with relevance to industry. Three papers remark on the importance of the integration of computer vision systems into a collaborative wire harness assembly process to make this more versatile as many types of wire harnesses exist. The literature review findings call for further research and technological developments in support of the wire harness manufacturing industry and its workers in four main categories: (i) Collaborative Robotics and Grippers, (ii) Ergonomics, (iii) Computer Vision Systems, and (iv) Implementation Methodologies.

Multi-objective complex product assembly scheduling problem considering parallel team and worker skills

The flow shop scheduling problem (FSP) is a classic shop scheduling problem with a strong engineering background. As an extension of FSP, the hybrid flow shop scheduling problem (HFSP) involves parallel machine scheduling, and the worker assignment problem on assembly lines (WAPAL) involves worker allocation. Parallel machine scheduling and multi-skilled and multilevel worker allocation are both involved in the actual assembly lines of complex products, but few studies have investigated them simultaneously. This work studies a complex product assembly line scheduling problem considering multi-skilled worker assignment and parallel team scheduling and takes the maximum completion time and the imbalance degree of team workload as the optimization objective. An integer programming model is proposed, and a hybrid coding method considers the worker assignment and task order. Three improved strategies based on a multiple objective evolutionary algorithm (MOEA) are proposed in the local search. Finally, 20 test instances are generated based on actual enterprise labor data, and the results based on the three strategies are compared with six MOEAs. The results show that the three strategies are superior in terms of the quality and distribution of solutions. The inverted generational distance (IGD) index value is increased by 49.97%, 47.89%, 47.08% respectively and the hypervolume (HV) index value is increased by 39.76%, 38.19%, 38.15% respectively.

Possibilities to Increase Assembly Line Productivity Using Different Management Approaches

A number of scientific methods are used to support productivity growth in companies, aimed at reducing waste, balancing assembly lines and supporting the introduction of automation into assembly processes. Their use in industrial practice is widespread, especially in large and medium-sized enterprises, and small businesses that use scientific methods to a limited extent. The aim of the research is to show the assembly process of throttle valves implemented in a small company, the effects of balancing the current assembly line and the effects of proposals of variant solutions on the automated assembly line and on the amount of hourly assembly production and costs per product. Within costs, two cost types are monitored: namely the hourly labor costs, and hourly machine costs. The sum of the hourly assembly line costs is determined by their sum. In the results section, the main sources of waste in the assembly process are identified, and eight proposals leading to the elimination of waste are processed. In the discussion, the individual proposals are evaluated in terms of the cost of one product, the hourly production of assembly and the tact times of assembly lines. The proposal that is evaluated as the best process is compared with the current state. The purpose of this article is to point out the advantages of the implementation of scientific methods in industrial practice, the achieved savings in the solved problem, and thus, to support those scientific methods in the management of assembly processes which are beginning to be used in greater extents by small businesses.

Digital twin-driven variant design of a 3C electronic product assembly line

Large-scale personalization is becoming a reality. To ensure market competitiveness and economic benefits, enterprises require rapid response capability and flexible manufacturing operations. However, variant design and production line reconfiguration are complicated because it involves the commissioning, replacement, and adaptive integration of equipment and remodification of control systems. Herein, a digital twin-driven production line variant design is presented. As a new technology, the digital twin can realize the parallel control from the physical world to the digital world and accelerate the design process of the production line through a virtual–real linkage. Simultaneously, the actual production line can be simulated to verify the rationality of the design scheme and avoid cost wastage. Four key technologies are described in detail, and a production line variant design platform based on digital twin is built to support rapid production line variant design. Finally, experiments using a smartphone assembly line as an example are performed; the results demonstrate that the proposed method can realize production line variant design and increase production efficiency.

Minimizing the Late Work of the Flow Shop Scheduling Problem with a Deep Reinforcement Learning Based Approach

In the field of industrial manufacturing, assembly line production is the most common production process that can be modeled as a permutation flow shop scheduling problem (PFSP). Minimizing the late work criteria (tasks remaining after due dates arrive) of production planning can effectively reduce production costs and allow for faster product delivery. In this article, a novel learning-based approach is proposed to minimize the late work of the PFSP using deep reinforcement learning (DRL) and graph isomorphism network (GIN), which is an innovative combination of the field of combinatorial optimization and deep learning. The PFSPs are the well-known permutation flow shop problem and each job comes with a release date constraint. In this work, the PFSP is defined as a Markov decision process (MDP) that can be solved by reinforcement learning (RL). A complete graph is introduced for describing the PFSP instance. The proposed policy network combines the graph representation of PFSP and the sequence information of jobs to predict the distribution of candidate jobs. The policy network will be invoked multiple times until a complete sequence is obtained. In order to further improve the quality of the solution obtained by reinforcement learning, an improved iterative greedy (IG) algorithm is proposed to search the solution locally. The experimental results show that the proposed RL and the combined method of RL+IG can obtain better solutions than other excellent heuristic and meta-heuristic algorithms in a short time.

Process Segmented based Intelligent Anomaly Detection in Highly Flexible Production Machines under Low Machine Data Availability

Anomaly detection is a key feature to monitor production systems an avoid downtimes, which has still not been implemented holistically. Especially in highly flexible plants or special process machines, conventional approaches like neuronal network classification or intelligent autoencoder fault detection are not suitable firstly due to the small amount and secondly due to the lack of labeling of data for each process. In this paper a novel concept is presented to segment different processes intelligently in the first step to find fine granular process patterns across process boundaries. Based on these patterns, anomaly detection and further classification are performed. A special feature is the integration of user knowledge, so that classification is possible even with a small amount of data. This approach is validated on an assembly line for electric motor production as well as in a handling robot. This paper shows results from real test series and thus demonstrates the practical suitability of the novel approach.

A case study on improving productivity in paint booth assembly

Currently, all automotive industries are faced with the need to respond to rapidly changing customer needs, their desires and the fluctuations in the market demand. During the plant visit and subsequent discussion made with the production department and also according to the operation process chart put up in the process study, it was noticed that the efficient time involved in the sub assembly process is less. Hence, this project work is conducted live to study the existing cycle time of a single model sub assembly line and suggesting improved methods to reduce the non-value-added activities, thereby reducing the cycle time in order to improve the efficiency of the sub assembly line and increase overall productivity. This case study is conducted in a leading garage equipment manufacturing industry in south India, which engages in manufacturing, designing and servicing garage equipment’s. Currently, this plant is manufacturing 25 paint booths (1.4 paint booth assembly per shift) which the company foresees a growth in demand for paint booth assembly and gearing to scale up its production rate to 40 paint booths (2.5 paint booth assembly in a shift) including Sub assembly 6 which has been newly added in the paint booth assembly to meet out its monthly requirement and achieved.

Models to evaluate the performance of high-mix low-volume manual or semi-automatic assembly lines

To address mass customisation demand trends, assembly line flexibility and productivity are critical. Industry 4.0 technologies could support assembly operations to this end. However, clear implementation methodologies are still lacking. This article presents two models for evaluating the most relevant Key Performance Indicators (KPIs) of manual or semi-automatic assembly lines, allowing to maximise the return of investment of any digital technology addition. MATLAB® was used to implement a parametric model, and FlexSim® was employed to build a discrete event simulation model. The models were validated using data from two industrial study cases from a global white goods manufacturer.

Considering physical workload and workforce diversity in a Collaborative Assembly Line Balancing (C-ALB) optimization model.

In comparison to the traditional usage of robots, Cobotization (Human-Robot collaboration) can be considered as an effective way to increase the productivity of assembly lines while ensuring job security and flexibility. However, successful implementation of human-robot collaboration scenarios requires adapted decision support tools. Workforce diversity can be mentioned as one of the factors that should be included to study its impact on both the performance of the production system and on ergonomics. Accordingly, in this research, a new bi-objective optimization model for the collaborative assembly line with Cobots is proposed to simultaneously minimize the cycle time and the physical workload of human operators. The workforce diversity of human operators is modeled through experience level and physical ability. To analyze the benefits of the developed model, a comparison between the different solutions from the Pareto front is conducted. The results show that the utilization of Cobots can reduce both cycle time and physical workload in the assembly line.

Improving the productivity of an assembly production line utilising lean tools and simulation: a case study

Improving the productivity of an assembly production line utilising lean tools and simulation: a case study

Assembly line productivity improvement through TPM by controlling line organisation efficiency and out of balance index: an empirical exploration

Assembly line productivity improvement through TPM by controlling line organisation efficiency and out of balance index: an empirical exploration

Integration of Waste Assessment Model and Lean Automation to Improve Process Cycle Efficiency in the Automotive Industry

Purpose: This study aims to improve Process Cycle Efficiency (PCE) by reducing waste in the assembly production line. This research is a case study conducted in a four-wheel vehicle manufacturing company to create a Lean production system. Methodology/Approach: This study uses the Waste Assessment Model (WAM) and Lean Automation integration methods carried out by 5 expert judgements in the selected four-wheeled vehicle industry. Findings: Based on the WAM method, this study found the biggest waste on the assembly line, namely transportation with a percentage of 20.44%. Improvements made with Lean Automation can increase the value of PCE from 56.76% to 63.62%. Research Limitation/Implication: This research is limited to one model, namely Multi Purpose Vehicle (MPV). This research provides benefits for companies related to waste reduction. For similar companies, this research can be input for manufacturing practitioners in improving manufacturing performance to compete in the global market. This Lean production can reduce manpower which has an impact on saving production costs. Originality/Value of paper: This paper provides added value related to the application of Lean terminology which aims to improve industrial automation-based manufacturing companies.

Dynamic model of a production assembly line as an absorbing markov chain

Dynamic model of a production assembly line as an absorbing markov chain

Multi-objective optimization of costs and energy efficiency associated with autonomous industrial processes for sustainable growth

Digital technologies are transforming the industrial landscape and disrupting traditional business models. New business opportunities related to Industry 4.0 are emerging, so companies must adapt to the new environment. This work puts forward a multi-objective optimization algorithm to improve productivity and reduce the costs and energy consumption of autonomous industrial processes with the aim of achieving sustainable growth. The processes analyzed encompass an assembly line production with robotic cells and the subsequent material handling systems (MHS) using autonomous guided vehicles (AGVs) for indoor transport. An efficient algorithm has been implemented to integrate and minimize industrial robot arm working times, AGVs travel times and their trajectory, and the energy consumed in industrial processes while maximizing global business profits when manufacturing different products in an indoor industrial environment. Furthermore, this is carried out by considering the kinematics and dynamics of autonomous industrial processes and sustainable strategies to ensure compliance with government policies on environmental issues. These objectives are in line with the European Union (EU) guidelines on reducing greenhouse gas (GHG) emissions, renewable energy share, and improvements in energy efficiency for climate change mitigation and adaptation policies. Based on the difference in energy consumption between optimized and unoptimized industrial processes, the economic benefits can be quantified in terms of GHG emission quotas, volume of fuel consumed, and the indirect benefits with respect to improving corporate brand image. The methodology presented here has been successfully applied to several real case studies covering different manufacturing processes, robotic operations, and products. The results show that higher profits and sustainable growth are achieved when this methodology is used. It helps design Flexible Manufacturing Systems (FMS) and leads to shorter working times and higher energy efficiency and annual profits. In addition, Pareto frontiers show the trade-off between profits and product manufacturing times for different case studies.

Research and Application of Flexible Manufacturing Line for Power Battery Module of New Energy Electric Vehicle

At present, due to the lack of national mandatory new energy vehicle power battery pack specifications and standards, so each production enterprise is fighting for itself, the size, connection mode and interface of the power battery pack are not unified, these factors seriously restrict the large-scale production and application of the power battery pack. Aiming at the characteristics of small batch and multi variety in the production process of new energy vehicle power battery pack, in order to realize the automatic assembly of multi variety power battery pack, on the basis of scientific and reasonable production process planning of power battery pack, a flexible automatic assembly and testing production line is developed, It is of great significance for power battery manufacturers to meet the needs of all kinds of customers and improve the level of intelligent manufacturing.

Design of Electrical Assembly Line Device for Motor Shell Processing Using PLC

In order to solve the problem of low automation of small-volume production of aluminium motor shells, an automated production assembly line is designed. The device is controlled by three PLCs for cutting, expanding, and punching. The MCGS designed touch screen implements modification of parameter settings, management of various sections, and monitoring of the entire device operating status. The system debugging results show that the device can complete the full-automatic production of motor shells processing process. The device is convenient for workers to operate the control system, and has the advantages of high automation degree, good stability, less labor and high efficiency.

Application of Computer Visual Recognition in Industrial Automation Assembly Production Line

Computer vision recognition technology refers to the technology of simulating human vision system with computer to realize the functions of object recognition, shape orientation confirmation, motion judgment and so on, in order to adapt, understand the external environment and control their own motion. The present situation of industrial automation in China is that the industries covered by full automation are relatively limited, mainly concentrated in the high value-added industries represented by automobiles, and most industries choose simple automation according to the tradeoff between automation effect and cost. In the course of industrial automation, the corresponding control technology and the most representative programmable controller, industrial computer and intelligent instrument device are developed according to the main characteristics of industrial field, among which computer vision recognition technology is more and more widely used in industrial automation.

Research on the Application of Automatic Production Line Based on Computer Control Technology

Information technology and computer technology in every field of society are playing a huge role, in the field of automatic production, computer technology with its strong operation and calculation ability and data processing ability, further promote the centralized control of automatic assembly line. In the future, it is an inevitable trend for computer system to replace human control. The application of computer technology can not only greatly improve the control efficiency, but also save manpower and material resources to a greater extent, and promote the progress of production level as a whole. Computer control technology is a computer-based technology. It is of great significance to analyze the application of computer control technology in automatic production line. Just as technology has changed our lives, it has also changed the way we produce and work. Nowadays, with the development of computer technology, network technology, information technology and other high and new technologies, all fields of the society have undergone earth-shaking changes, including the field of industrial production. Now the industrial production has realized the automatic assembly line production, and in order to better control the automatic assembly line production, in order to ensure its production efficiency, safety and stability, it must be applied to the computer control technology. At the same time, the application of computer control technology also helps to save human and material resources, thus saving the overall production cost and improving the economic efficiency of enterprises.

An Imperfect Legacy

An Imperfect Legacy