Production Line Capacity Research Articles

Quality Improvement Project Selection Using Fuzzy AHP and TOPSIS to Support Lean Six Sigma at PT ABC

This research aims to improve project quality at PT ABC by integrating the Fuzzy Analytical Hierarchy Process (F-AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) within the Lean Six Sigma framework. This method assesses and selects quality improvement projects by considering uncertainty and complexity in decision-making. The Fuzzy AHP approach is used to flexibly assign criteria weights, while TOPSIS is used to rank projects based on performance scores relative to the ideal solution. This research aims to select the most suitable Lean Six Sigma project using the MCDM fuzzy AHP and TOPSIS approaches at PT ABC. There are three alternative quality improvement projects and three assessment criteria. The data processing results using Fuzzy AHP and TOPSIS showed that the most influential criterion was the impact criterion, with a value of 0.665. Overall, the order of influencing criteria is cost (0.260) and time (0.075). Based on a review of all criteria, the project to increase the drive plate production line (A) capacity was ranked first with a value of 0.772. Second place is the project to increase capacity and consolidate rear axle assemblies A and B with a value of 0.5529. Finally, the third is the process innovation and integrated manufacturing project to strengthen the business with a value of 0.4053.

Digital Twin-Driven Multi-Factor Production Capacity Prediction for Discrete Manufacturing Workshop

Traditional capacity forecasting algorithms lack effective data interaction, leading to a disconnection between the actual plan and production. This paper discusses the multi-factor model based on a discrete manufacturing workshop and proposes a digital twin-driven discrete manufacturing workshop capacity prediction method. Firstly, this paper gives a system framework for production capacity prediction in discrete manufacturing workshops based on digital twins. Then, a mathematical model is described for discrete manufacturing workshop production capacity under multiple disturbance factors. Furthermore, an innovative production capacity prediction method, using the “digital twin + Long-Short-Term Memory Network (LSTM) algorithm”, is presented. Finally, a discrete manufacturing workshop twin platform is deployed using a commemorative disk custom production line as the prototype platform. The verification shows that the proposed method can achieve a prediction accuracy rate of 91.8% for production line capacity. By integrating the optimization feedback function of the digital twin system into the production process control, this paper enables an accurate perception of the current state and future changes in the production system, effectively evaluating the production capacity and delivery date of discrete manufacturing workshops.

Research on defect detection of bottle cap interior based on low-angle and large divergence angle vision system.

During the machine vision inspection of the inner section of bottle caps within pharmaceutical packaging, the unique conca bottom and convex side walls often create obstructions to the illumination. Consequently, this results in challenges such as irregular background and diminished feature contrast in the image, ultimately leading to the misidentification of defects. As a solution, a vision system characterized by a Low-Angle and Large Divergence Angle (LALDA) is presented in this paper. Using the large divergence angle of LED, combined with low-angle illumination, a uniform image of the side wall region with bright-field characteristics and a uniform image of inner circle region at the bottom with dark-field characteristics are obtained, thus solving the problems of light being obscured and brightness overexposure of the background. Based on the imaging characteristics of LALDA, a multi-channel segmentation (MCS) algorithm is designed. The HSV color space has been transformed, and the image is automatically segmented into multiple sub-regions by mutual calculation of different channels. Further, image homogenization and enhancement are used to eliminate fluctuations in the background and to enhance the contrast of defects. In addition, a variety of defect extraction methods are designed based on the imaging characteristics of different sub-regions, which can avoid the problem of over-segmentation in detection. In this paper, the LALDA is applied to the defect detection inside the cap of capsule medicine bottle, the detection speed is better than 400 pcs/min and the detection accuracy is better than 95%, which can meet the actual production line capacity and detection requirements.

Assembly line balancing and capacity evaluation based on interval grey processing time

PurposeAssembly line is a common production form and has been effectively used in many industries, but the imprecise processing time of each process makes production line balancing and capacity forecasting the most troublesome problems for production managers. In this paper, uncertain man-hours are represented as interval grey numbers, and the optimization problem of production line balance in the case of interval grey man-hours is studied to better evaluate the production line capacity.Design/methodology/approachFirst, this paper constructs the basic model of assembly line balance optimization for the single-product scenario, and on this basis constructs an assembly line balance optimization model under the multi-product scenario with the objective function of maximizing the weighted greyscale production line balance rate, second, this paper designs a simulated annealing algorithm to solve problem. A neighborhood search strategy is proposed, based on assembly line balance optimization, an assembly line capacity evaluation method with interval grey man-hour characteristics is designed.FindingsThis paper provides a production line balance optimization scheme with uncertain processing time for multi-product scenarios and designs a capacity evaluation method to provide managers with scientific management strategies so that decision-makers can scientifically solve the problems that the company's design production line is quite different from the actual production situation.Originality/valueThere are few literary studies on combining interval grey number with assembly line balance optimization. Therefore, this paper makes an important contribution in this regard.

Augmented reality and indoor positioning based mobile production monitoring system to support workers with human-in-the-loop

With the increasing demand for product customization, the exponential increase in large-scale and small-batch production orders has yielded new challenges for the capacity of traditional production lines. Due to the information redundancy and complex production process on the production site of the factory, the traditional monitoring system is incapable of meeting the information interaction requirements between the factory management level and the executive level. Meanwhile, the traditional augmented reality (AR) based on image recognition is not suitable in the complex industrial environments. To address the gap, we propose a novel mobile production monitoring system (AIMPMs) with human-in-the-loop control by leveraging the cutting-edge AR and indoor positioning technique. In the proposed system, Ultra-wideband (UWB) and Inertial Measurement Unit (IMU) fusion indoor positioning technology is proposed, which provides accurate indoor positioning information for the production factors in the factory. Subsequently, we build the lightweight indoor map for positioning that can serve as the location reference and path planning, and a nearest-neighbor decision algorithm with double rejection decision (NN-DRD) is proposed to match the positioning features to trigger virtual monitoring information. Finally, the AIMPMs is applied in a hydraulic cylinder factory to verify its enforceability and effectiveness, and the human factors evaluation model and index system are constructed to evaluate two systems, (1) the mobile monitoring system based on positioning information, and (2) the mobile monitoring system based on image recognition, respectively. The experimental results indicate that after the application of AIMPMs, the physiological and mental fatigue of the production personnel is immensely decreased. Therefore, the system realizes a smarter and highly humanized human-machine interaction mode with human-in-the-loop control.

Surface Mounted Production Line Capacity Prediction Based on Data Driven

Capacity prediction of surface mount production lines is important for improving productivity, dynamic production scheduling, and optimizing production structure. An integrated mutual information-cuckoo search-extreme learning machine (MI-CS-ELM) prediction model is proposed for the impact of nonlinear and high-dimensional features of surface-mounted production lines on capacity. Firstly, the features affecting the production capacity are ranked based on the mutual information method, and the predictive input data set is reconstructed. Secondly, the input parameters of the prediction model are adjusted by the cuckoo search algorithm and the capacity prediction model is built based on an extreme limit learning machine. Finally, the rationality of the proposed method is verified by an example to guide capacity planning and production scheduling optimization.

Review on Thermal Energy Audit of Pyro-Processing Unit of a Cement Plant

Energy consumption in cement factories is an important issue for the government as well as private organizations. The cement manufacturing industrial sector has become the worldwide energy consumer accounting for over 40% of overall energy consumption by the industrial sub-sector. Most of the thermal energy consumption by a cement manufacturing plant occurs in the Pyro-processing unit. Thus, the energy audit of the cement plant is an essential exercise to promote energy retrofitting measures. The aim of the energy audit is to reduce energy consumption in the plant, reduce energy costs and identify possible Energy Conservation and Management Opportunities (ECMOs). The aim of this study was to review the techniques of energy auditing which include Mass (Material) balance and Energy balance by considering energy conservation in the form of thermal energy that helps to fill the gap in energy efficiency improvement, policy development, and environmental analysis. Using the operational data of Kiln system of Messobo Cement obtained from the literature, the heat losses were quantified for major energy consuming components of the system using both the mass and thermal energy balance approach. The production line's capacity for clinker was 145.4 tons per hour, and both burners received a combined 25 tons of coal per hour. Energy balance tests were conducted in all areas of the pyro processing systems, and the findings revealed significant energy losses from the surface of the kiln systems, kiln exhaust, and cooler exhaust.

An efficient production planning approach based demand driven MRP under resource constraints

Production plans based on Material Requirement Planning (MRP) frequently fall short in reflecting actual customer demand and coping with demand fluctuations, mainly due to the rising complexity of the production environment and the challenge of making precise predictions. At the same time, MRP is deficient in effective adjustment strategies and has inadequate operability in plan optimization. To address material management challenges in a volatile supply-demand environment, this paper creates a make-to-stock (MTS) material production planning model that is based on customer demand and the demand-driven production planning and control framework. The objective of the model is to optimize material planning output under resource constraints (capacity and storage space constraints) to meet the fluctuating demand of customers. To solve constrained optimization problems, the demand-driven material requirements planning (DDMRP) management concept is integrated with the grey wolf optimization (GWO) algorithm and proposed the DDMRP-GWO algorithm. The proposed DDMRP-GWO algorithm is used to optimize the inventory levels, shortage rates, and production line capacity utilization simultaneously. To validate the effectiveness of the proposed approach, two sets of customer demand data with different levels of volatility are used in experiments. The results demonstrate that the DDMRP-GWO algorithm can optimize the production capacity allocation of different types of parts under the resource constraints, enhance the material supply level, reduce the shortage rate, and maintain a stable production process.

ANALISIS KAPASITAS PRODUKSI PADA LINI PRODUKSI BARU FORD P702 HVPO DENGAN PENDEKATAN METODE ROUGH CUT CAPACITY PLANNING (STUDI KASUS DI PT CSB)

ABSTRACTThis research is to analyze capacity requirements and availability on the production line. This research in PT CSB project FORD P702 HVPO production line. Data analysis used the Rough Cut Capacity Planning (RCCP) method by measuring work (time study), forecasting, aggregate planning, master production schedule and capacity analysis with RCCP.Based on research, standard time is 745 seconds / unit for new prodject FORD P702 HVPO. The best forecasting method is use Single Moving Average with an MAD error value of 0.04 and MSE error value of 0.021. Aggregate planning calculation results is 27144 units per year with cost of Rp 49,563,348 per year. And the conclusion is the capacity of the FORD P702 HVPO production line is sufficient and feasible to meet customer needs. This research is calculated based on the total production capacity of 19,958,400 seconds per unit in 1 year and the total required capacity of 18,618,775 seconds per unit in 1 year.

Comparative Study on the Influence of U-Shaped Self-Organizing Production Line Configuration on Capacity

There are three typical representatives of U-shaped selforganizing production line, namely U-shaped Travelling, Chasing- Overtaking, Cellular Bucket Brigade. The equipment, placed according to the process sequence, and the distance between the equipment form a Ushaped production line configuration. The former forms the process imbalance variable, and the latter forms the aisle width variable. For this, a simulation experiment with process imbalance and aisle width as independent variables and production line capacity as dependent variable was designed. The Plant-Simulation® simulation platform was used to obtain experimental data and verify it. The results show that Chasing- Overtaking capacity is the highest under the same conditions. The production capacity of Cellular Bucket Brigade line and U-shaped traveling line is lower than that of CO line by more than 20%; and under the discrete system, the three self-organized production lines are not affected by configuration factors.

Interaction between the Government and the Market and Enterprise Strategy Realization: Empirical Evidence of China’s Road Confidence in BOE

This paper discusses the specific process and mechanism of how the market realizes resource allocation under the guidance of the government and acts on the realization of micro enterprise strategy. After continuous tracking, we find that BOE has actively carried out layout around the national strategy, invested in many places, built production lines, and continuously strengthened innovation investment under the interaction of the government and the market. Through more than ten years of efforts, it has formed a relatively reasonable production line and production capacity layout nationwide, and finally made outstanding achievements in market, technology, brand, export and global competitiveness.Based on the theoretical tools of the relationship between the government and the market, the relationship between the central government and the local government, and the life cycle of enterprises, this paper makes an essential analysis of the case phenomenon and draws the following conclusion: （1） In China, the government is not opposed to the market. Government support and market mechanism are important forces to promote the realization of national strategy at the micro level. It is also the concrete embodiment of China’s economic development road confidence. （2） Coordinating the relationship between the central government and the local government is an important guarantee for maintaining the unified leadership of the central government, mobilizing the enthusiasm of the local government and the market, and promoting the rational cross-regional distribution of enterprise investment. （3） The innovation effect of the interaction between government support and market mechanism has significant periodicity and hysteresis, and its economic effect is the result of enterprises’ multi-cycle development. Therefore, the realization of the strategic goal of the interaction between the government and the market needs a long-term process.The contribution of this paper is that it breaks through the opposite perspective on the understanding of the relationship between the government and the market, reveals the experience of China’s economic development with the interactive operation mechanism in real cases, and provides a realistic basis for China’s road confidence.

Perancangan Kapasitas Produksi Produk Electronic Control Unit (Ecu)

The export demand for Electoric Control Unit (ECU) products, which continued to increase by approximately 25% in December 2014, made the company have to review its production capacity. Based on current production capacity data, it is known that the process cycle time is 64.9 seconds while the takt time needed to meet consumer demand is 39.4 seconds for the first production line. With working time included in working hours overtime, this first-line capacity cannot meet production demands. Work measurement is done to get actual time data for capacity calculation. Man machine chart is one of the tools used to determine the production line capacity with the current number of machines and workers. To be able to fulfill the production demand, a capacity design with 2 proposed improvements is carried out, namely: adding a working time of one shift for the first production line or balancing work time between lines. By calculating the results obtained and the costs incurred, the proposal for balancing work time between lines becomes more effective to do.

A framework and implementation of Customer Platform-connection manufactory to service (CPMS) model in product service system

With the continuous improvement of living standards, customers are gradually pursuing products which are individualization and entertainment. The traditional large-scale manufacturing mode cannot meet the individual needs of customers. The production mode of the enterprises has been changed from the traditional inventory mode to the customization manufacturing mode driven by the customer orders. Furthermore, the simple customization model cannot meet the industrial needs in the open and networked era. Therefore, there is a lack of an innovative manufacturing mode that not only meets the individual needs of customers, but also adapts to today’s open and networked environment. In this paper, a new customization model was proposed, which is a continuously improved customization model called CPMS (Customer Platform-connection Manufactory to Service). By means of research methodology of literature review and analysis, the birth, concept, and evolution of CPMS in PSS are discussed. Through analysing the development of industry, combining with the existing analysis and projects we involved in, and the method of system engineering analysis, an overall framework of CPMS model is derived. At last, a case study for implementation of CPMS in the car industry has been given. Under this model, enterprises can improve the flexible production capacity of production line, reduce the production cost, reduce inventory, improve the modular configuration of products, and etc. Moreover, it can provide some reference value for enterprises to plan, design, implement and apply a new customization production model that conform to the requirements of the new era of open and networked.

Work Measurement Study to Increasing Productivity of Production Line

The main goal of the paper is to propose solution toward capacity improvement of assembly process on a selected production line. The major content is focused on Basic Most method and its application in improvement process. There is a theoretical expectation that after applying Basic Most method to the assembly process, the capacity of production line would increase about twenty percentages. Motion and Time studies are often applied for improvements in efficiency of assembly processes. First, Process Screen method is used for gaining the information about process behaviour and its individual, partial and total duration. The final solution consists of new layout design of working station at the selected production line.

Analysis and Improvement of an Assembly Line in the Automotive Industry

In a market as competitive as the automotive industry, it becomes increasingly important for the organizations to adopt a culture of continuous improvement, which should cross-over all stakeholders in the organization. The continuous improvement of the processes, the increase in efficiency, and the elimination of waste, leads to a considerable increase in market competitiveness, not only economically, but also technologically. The focus of this work was the optimization of a production line, with the main goal being the increase of its productive capacity, so that it can comply with customer’s requests. Thus, it was defined as a goal of this project: to increase the productive capacity to 1800 parts/day. The methodologies used were based on several continuous improvements and lean techniques, such as line balancing, standard work, visual management and 5S. The work developed allowed an increase of 37% of the production line capacity and an increase of 22% in the OEE of the production line.

Production line 3D visualization monitoring system design based on OpenGL

New production line management technologies are required and adopted recently with the development of modern manufacturing industry. In this study, a production line three-dimensional (3D) visualization monitoring system based on OpenGL modeling, open database connectivity (ODBC), and database management technology is established on a VC++6.0 platform to satisfy effective production. A client/server model is adopted in the system, and data on processing information, interactive operation, and failure process are stored in the server side database. A client reads the workpiece process information from the server, and the machining process of every workpiece is visually represented in the form of 3D visualization. Production line 3D visualization provides production capacity simulation to optimize the parameter settings. When compared with the analysis results of production line capacity, the key parameters possess the same optimal values, and this proves the accuracy of production line 3D visualization monitoring system. The system provides effective data support for production line monitoring and management in enterprises.

A Real Time Object Recognition and Counting System for Smart Industrial Camera Sensor

In the industry 4.0, factories around the world grow automated and intelligent, and where smart camera plays an important role. Smart camera is equipped with processor, memory, communication interface, and operating system, so it can process large amounts of data in advance to assist follow-up automatic inspection and judgment. Additionally, since smart camera is an independent system, it will not affect the original system of factories, which is an immense advantage in troubleshooting. Besides, thanks to technology breakthroughs in recent years, using Graphics Processing Unit (GPU) to implementing tons of parallel computing helps to significantly boost the overall efficiency. Therefore, when a rising number of factories consider improving production capacity of production lines, how to use GPU to assist the improvement is an important issue. Based on this scenario, this paper used NVidia Tegra TX1 platform with 256 GPU CUDA cores and Quad-core ARM Cortex A57 processor and Basler USB 3.0 industrial camera to simulate a smart industrial camera, which has GPU and can perform a myriad of complex computations. This paper designed how to recognize and count objects in a real time manner in a high-speed industrial inspection environment with large volumes of data, so as to verify the concept (smart camera with GPU cores) we proposed. The experimental results proved our ideas, and the software design architecture provided in this paper is a simple and efficient design. In the future application in the Internet of Things or the Internet of Everything, this structure can be a valuable reference.

Studying the rheological properties and the influence of drag reduction on a waxy crude oil in pipeline flow

The present work studies the effect of a commercially type of drag reducing agent on the crude oil production flow lines located in the Egyptian western desert (Fagour field) and owned by Khalda Petroleum Company. The drag reducing agent used in this study is a high molecular weight poly alpha olefin prepared by emulsion polymerization technique and supplied under trade name of LP-111. The results showed that this drag reducing agent (DRA) has great effects on the pressure drop and fanning factor. After the field application of 60ppm of the DRA, the pressure drop was decreased by 36% at the pipeline capacity of 18,804bbl/day. The fanning number and shear stress were decreased by the same percentage of 47%. The capacity of production line can be increased by 38% all over the two pipeline section due to the great reduction of pressure drop.The rheological behaviors of tested waxy crude oil were studied at different temperatures (varies from 67 to 102°F) and different DRA concentrations (10, 20, 30, 40, and 50ppm). The results showed that at all constant DRA concentrations, the viscosity highly decreased until 80°F (above pour point by 15°F). However, by increasing the DRA concentration, the viscosity is increased at temperatures lower than 80°F. This is because the DRA is a high molecular weight polymer which participates in increasing viscosity by increasing its concentration. After 80°F, the DRA concentration has an insignificant effect on viscosity. So the effect of the DRA is not in reducing viscosity but mainly in reducing the degree of turbulence energy. The field studies were performed at a normal temperature of tested pipeline sections (100°F). The tested DRA has an improving effect on reducing the pressure drop of pipeline which leads to reduction in crude oil pumping energy or an increase in the pipeline capacity with a high efficiency of the DRA.

Production line capacity planning concerning uncertain demands for a class of manufacturing systems with multiple products

In this paper, we study a class of manufacturing systems which consist of multiple plants and each of the plants has capability of producing multiple distinct products. The production lines of a certain plant may switch between producing different kinds of products in a time-sharing mode. We optimize the capacity configuration of such a system0s production lines with the objective to maximize the overall profit in the capacity planning horizon. Uncertain demand is incorporated in the model to achieve a robust configuration solution. The optimization problem is formulated as a nonlinear polynomial stochastic programming problem, which is difficult to be efficiently solved due to demand uncertainties and large search space. We show the NP-hardness of the problem first, and then apply ordinal optimization (OO) method to search for good enough designs with high probability. At lower level, an mixed integer programming (MIP) solving tool is employed to evaluate the performance of a design under given demand profile.

Exponential Smoothing for Multi-Product Lot-Sizing With Heijunka and Varying Demand

Abstract Here we discuss a multi-product lot-sizing problem for a job shop controlled with a heijunka box. Demand is considered as a random variable with constant variation which must be absorbed somehow by the manufacturing system, either by increased inventory or by flexibility in the production. When a heijunka concept (production leveling) is used, fluctuations in customer orders are not transferred directly to the manufacturing system allowing for a smoother production and better production capacity utilization. The problem rather is to determine a tradeoff between the variability in the production line capacity requirement and the inventory level.