Optimization of the Lean Production Process Using the Virtual Manufacturing Cell

2014 ◽  
Vol 1036 ◽  
pp. 858-863 ◽  
Author(s):  
Agnieszka Sękala ◽  
Aleksander Gwiazda ◽  
Zbigniew Monica ◽  
Wacław Banaś
Keyword(s):  
Production Process ◽  
Heuristic Algorithms ◽  
Lean Production ◽  
Virtual Manufacturing ◽  
Basic Relation ◽  
Rule Base ◽  
Optimization Approach ◽  
Distributed Robotics ◽  
Manufacturing Cell ◽  
Advanced Computer

The most important element of the production process is the optimization of the conducted operations. It is particularly important for the lean production process. In the paper is presented the analysis of the optimization approach using the CAE systems, the multi-agents systems (MAS) and the distributed robotics (DR) systems. Using the CAE techniques it is possible to elaborate the virtual environment in which the manufacturing cell is designed. The interaction between the virtual model and the process rule base allow improving the design of the existing standard machining technology. The MAS approach let to create the structure of the manufacturing process, taking into account both the machining stands and transport units according to the elaborate technological process. Finally the utilization of the DR approach for the optimization of transport operations including the heuristic algorithms. Moreover in the paper are presented the results of the investigations of analyzed problem on the base of complex production line for the cylindrical elements. The simulations and other analysis have been conducted in advanced computer systems. Also the basic relation between mentioned systems are discussed.

scholarly journals MANAGEMENT ACCOUNTING TOOLS FOR IMPROVEMENT OF PRODUCTION PROCESS - LEAN PRODUCTION SYSTEM

2019 ◽  
Vol 31 (5) ◽  
pp. 1391-1396
Author(s):  
Gordana Stojmenović ◽  
Lyubcho Varamezov
Keyword(s):  
Production Process ◽  
Continuous Improvement ◽  
Production System ◽  
Customer Value ◽  
Production Systems ◽  
Management Accounting ◽  
Lean Production ◽  
Continuous Process ◽  
Added Value ◽  
Modern Business

Business in modern business conditions requires a continuous process of improvement and investment in all activities in the company. In order to survive on the market, resist the challenges of competition, but also the demands of customers, companies are constantly innovating the production process in an effort to improve all the company's activities. One of the production systems that proved to be suitable for continuous improvement and improvement of the production process is Lean production system. It represents the way companies react to the challenges of the present and the future. The Lean production system offers a variety of instruments, and for their implementation and application, managers are at all levels of responsibility and responsibility. Bearing this in mind, it can be said that the Lean production system is part of the management accounting. In addition, it represents a complete philosophy of thinking and action, which results in significant results by adequate application. The condition and the assumption that this management philosophy will lead to proper effectiveness and efficiency and enable them to continually improve in the function of maximizing profits is the authorization of employees to engage in the process of continuous improvement and decision-making. Lean is based on certain principles and philosophies, including customer value, value flow mapping, continuous flow, system requirements, and continuous improvements. Lean focuses on the added value. Lean's principle is a continuous search for perfection, perfection in production and business cooperation, with complete elimination of losses. Companies that implement the Lean Concept are constantly looking for ways to continually improve their efficiency, reduce costs and improve the quality of their products.

scholarly journals PERENCANAAN DAN PENGENDALIAN KAPASITAS PRODUKSI PRODUK RAKITAN RADIO TIPE SOUNESS SNI 4250

2018 ◽  
Vol 20 (1) ◽  
pp. 40-47
Author(s):  
Abdul Rahim Matondang ◽  
Widodo Widodo
Keyword(s):  
Production Process ◽  
Production Planning ◽  
Capacity Planning ◽  
Pure Strategy ◽  
Raw Material ◽  
Optimization Approach ◽  
Production Schedule ◽  
Middle Term ◽  
Individual Product

Production system take an important role in industries, especially in manufacturing industries. This role determine the keys of successful company. Production process is an activity which produce finished product from raw material that involve machine, energy, and technique knowledge. Production process is real activity and can be seen by human being. The problems those always be faced in indutries management’s are the arrangement of production schedule, such lack of inventory or overstock once the settlement of production process isn’t on time. Production planning and control is activity to determine what product that will be produced, how many product that will be produced and how many labors needed in production processes. By using production planning and control’s method, those problems can be minimalized. Aggregate planning is one of production planning a.nd control’s method. By using this method, production planning could be done by using unit of replacement product so that the output of this planning isn’t declared in individual product. So, the output of aggregate planning isn’t planning in form of individual product but aggregate’s product. There are some strategies on aggregate planning such as pure strategy on aggregate planning and mixed strategy on aggregate planning. In this research, method of aggregate planning that used is optimization approach by linier rule. This method used to make long term planning and middle term planning. Long term planning consists of product forecasting and aggregate planning. The middle term planning consist of master production schedule and rough cut capacity planning. The result of this research is capacity needed and capacity available to determine which work center is drum and which isn’t. Conclusion of this research that capacity of each work center in perioad january to december 2018 is non drum. This indicate the good scheduling in capacity planning.

A New Optimization Approach to Clustering Fuzzy Data for Type-2 Fuzzy System Modeling

2012 ◽  
pp. 499-508
Author(s):  
Mohammad Hossein Fazel Zarandi ◽  
Milad Avazbeigi
Keyword(s):  
Fuzzy Clustering ◽  
Fuzzy System ◽  
Distance Measure ◽  
System Model ◽  
Rule Base ◽  
Optimization Approach ◽  
Fuzzy Data ◽  
System Models ◽  
Fuzzy System Models

This chapter presents a new optimization method for clustering fuzzy data to generate Type-2 fuzzy system models. For this purpose, first, a new distance measure for calculating the (dis)similarity between fuzzy data is proposed. Then, based on the proposed distance measure, Fuzzy c-Mean (FCM) clustering algorithm is modified. Next, Xie-Beni cluster validity index is modified to be able to valuate Type-2 fuzzy clustering approach. In this index, all operations are fuzzy and the minimization method is fuzzy ranking with Hamming distance. The proposed Type-2 fuzzy clustering method is used for development of indirect approach to Type-2 fuzzy modeling, where the rules are extracted from clustering fuzzy numbers (Zadeh, 1965). Then, the Type-2 fuzzy system is tuned by an inference algorithm for optimization of the main parameters of Type-2 parametric system. In this case, the parameters are: Schweizer and Sklar t-Norm and s-Norm, a-cut of rule-bases, combination of FATI and FITA inference approaches, and Yager parametric defuzzification. Finally, the proposed Type-2 fuzzy system model is applied in prediction of the steel additives in steelmaking process. It is shown that, the proposed Type-2 fuzzy system model is superior in comparison with multiple regressions and Type-1 fuzzy system model, in terms of the minimization the effect of uncertainty in the rule-base fuzzy system models an error reduction.

The Virtual Manufacturing Cell

1982 ◽  
Vol 15 (8) ◽  
pp. 207-215 ◽  
Author(s):  
C.R. McLean ◽  
H.M. Bloom ◽  
T.H. Hopp
Keyword(s):  
Virtual Manufacturing ◽  
Manufacturing Cell

Approximation Performance of BP Neural Networks Improved by Heuristic Approach

2013 ◽  
Vol 411-414 ◽  
pp. 1952-1955 ◽  
Author(s):  
Shuo Ding ◽  
Xiao Heng Chang ◽  
Qing Hui Wu
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Bp Neural Network ◽  
Numerical Optimization ◽  
Heuristic Algorithms ◽  
Nonlinear Function ◽  
Heuristic Approach ◽  
Optimization Approach ◽  
Bp Neural Networks ◽  
The One

Among all improved BP neural network algorithms, the one improved by heuristic approach is studied in this paper. Firstly, three types of improved heuristic algorithms of BP neural network are programmed in the environment of MATLAB7.0. Then network training and simulation test are conducted taking a nonlinear function as an example. The approximation performances of BP neural networks improved by different numerical optimization approaches are compared to aid the selection of proper numerical optimization approach.

scholarly journals Research and Implementation of Lean Production Mode in Shipbuilding

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 2071
Author(s):  
Tingxin Song ◽  
Jincheng Zhou
Keyword(s):  
Production Process ◽  
Large Scale ◽  
High Efficiency ◽  
Lean Production ◽  
Original Data ◽  
Utilization Rate ◽  
Production Cycle ◽  
Manufacturing Execution System ◽  
High Flexibility ◽  
Manufacturing Execution

This paper studies the production process of a shipbuilding enterprise. The company suffers from long manufacturing cycle, low utilization rate of personnel and an unbalanced production line. To solve these problems, the lean shipbuilding mode, mainly divided into shipbuilding work breakdown, production plan and virtual flow operation in this paper, is put forward, which combines the lean production and modern information management technology with shipbuilding. Supported by the theory of work breakdown structure and task package scheduling, the shipbuilding task package is reasonably divided. The priority of task package manufacturing is determined by calculating the task package manufacturing sequence coefficient, and a reasonable number of operators is calculated to ensure the continuity of segmented manufacturing. After determining the manufacturing priority of the task pack and the number of allocable personnel, the corresponding work can be scheduled. Production planning drives all production activities of the shipbuilding enterprise, and just-in-time production is achieved through the reasonable arrangement of these production plans, thus reducing the waste of personnel and time. Then, the virtual flow operation is carried out, which can achieve high efficiency of flow production and high flexibility of fixed workstation production during the production process of large-scale and heavy-duty products. The virtual assembly production system of the workshop is established according to the characteristics of shipbuilding operation and the actual production situation. On this basis, a lean shipbuilding manufacturing execution system for small and medium-sized shipbuilding enterprises is developed to achieve lean production in a shipbuilding workshop. Through the implementation of the lean shipbuilding mode based on task package scheduling and its manufacturing execution system, compared with the original data, the ship production cycle is reduced to 76.7%, the number of workers is reduced by 16.7% and the production balance rate is up to 81%.

Lean manufacturing: The history and our time

2021 ◽  
Vol 17 (9) ◽  
pp. 1650-1669
Author(s):  
Ekaterina N. STRIZHAKOVA ◽  
Dmitrii V. STRIZHAKOV
Keyword(s):  
Production Process ◽  
Lean Manufacturing ◽  
Positive Impact ◽  
Manufacturing Sector ◽  
Lean Production ◽  
Economic Security ◽  
Production Model ◽  
Planning System ◽  
Industrial Enterprises ◽  
Production Concept

Subject. The article discusses the use of the lean production concept at the production enterprise. Objectives. We evaluate the existing lean production toolkit, determine opportunities for their implementation and possible difficulties. Methods. Methodologically, the study is based on the comparative analysis of methods that constitute the lean production system. Results. We review one of the economic security aspects for Russia, such as an increased production competitiveness due to the ubiquitous implementation and use of lean production instruments. We conducted an historical analysis of the origination and development of the production process approach. Some lean production tools and aspects were proved to have been designed and actively used in the USSR manufacturing sector since the 1960s. The lean production concept was found to become very appropriate for enterprises. We analyzed the continuing production planning system by A.S. Rodov, which were in use ans proved its high cost efficiency at the USSR industrial enterprises. We also delved into the profit generating production process that was put in place in Toyota. The article provides the comparative description of modern lean production methods and concludes on their future use. Conclusions. Having compared the Soviet lean production model and the classical Japanese one, we concluded on the use of such production process methods that really went beyond their time. In the mean time, the Soviet model was simpler to use and implement. Based on the overview of modern lean production tools that evolved from the Soviet and Japanese lean production theories, we believe that the lean production principles and methods will have a positive impact on the efficiency and competitiveness of the national manufacturing sector.

Heuristic Approaches in Clustering Problems

2018 ◽  
pp. 107-124 ◽  
Author(s):  
Onur Doğan
Keyword(s):  
Local Minimum ◽  
Heuristic Algorithms ◽  
Minimum Point ◽  
Optimization Approach ◽  
Similar Data ◽  
Heuristic Approaches ◽  
Clustering Problem ◽  
Local Minimum Point ◽  
Np Hard Problem ◽  
Short Time

Clustering is an approach used in data mining to classify objects in parallel with similarities or separate according to dissimilarities. The aim of clustering is to decrease the amount of data by grouping similar data items together. There are different methods to cluster. One of the most popular techniques is K-means algorithm and widely used in literature to solve clustering problem is discussed. Although it is a simple and fast algorithm, there are two main drawbacks. One of them is that, in minimizing problems, solution may trap into local minimum point since objective function is not convex. Since the clustering is an NP-hard problem and to avoid converging to a local minimum point, several heuristic algorithms applied to clustering analysis. The heuristic approaches are a good way to reach solution in a short time. Five approaches are mentioned briefly in the chapter and given some directions for details. For an example, particle swarm optimization approach was used for clustering problem. In example, iris dataset including 3 clusters and 150 data was used.

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