Continuous Improvement Of Production Processes Research Articles

Effect of Vacuum Brazing Conditions of Inconel 718 Superalloy Sheets on Microstructure and Mechanical Properties of Joints

Vacuum furnace brazing is one of the most commonly used joining processes in the aerospace industry, utilized in the manufacturing of the complex components of turbine jet engines, working in both their cold and hot sections. The modern aerospace industry demands continuous improvement of production processes to enhance the engine performance, while ensuring its reliability. Therefore, a better understanding of the processes that shape the properties of engine assemblies joints is crucial. This paper presents an analysis of the influence of key brazing process parameters – brazing time and gap width – on the microstructure and mechanical properties of Inconel 718 superalloy joints obtained with the Palnicro 36M filler alloy. The analysis was conducted basing on results from SEM/EDS analysis and peel, shear and spreadability tests.

FORMATION «OF THE CARD-PROCEDURE OF» INTELLIGENT ANALYSIS OF THE PRODUCTION PROCESS

Annotation. The importance of continuous improvement of production processes occurring in the internal environment of the organization is necessary both for the development of the organization and for the successful functioning of the entire country. Taking into account the constant development of information systems, the article discusses production systems with high complexity and variety of processes. Thus, the question arises about the methods of analyzing production processes. The intellectual analysis tool in question assumes dynamic data display of the entire production system. The card procedure consists of three stages. The first stage involves drawing up this map. At the second stage, the analysis of the data obtained takes place, and the third stage implies the improvement of the production process. The presented procedure card promises wide application in production conditions. In addition, the article discusses the main problems associated with the introduction of intelligent analysis of production processes.

Continuous production improvement concept for shipbuilding enterprises

Aim. The presented study aims to investigate a relevant quality management method and to propose ways of adapting the continuous production improvement methodology to the operating conditions of a shipbuilding enterprise.Tasks. The authors describe a productive management system and effective lean production tools; popularize commitment to continuous improvement at every workplace and in every production process of a shipbuilding enterprise; describe an algorithm for the continuous improvement of production processes to increase labor productivity.Methods. This study uses systems analysis, synthesis, and methods of logical analysis to systematize existing approaches, basic tools, and methods of quality management, in particular the concept of continuous improvement for enterprises.Results. Adapting the concept of continuous improvement for shipbuilding enterprises and becoming a lean enterprise requires not only a special management style, but also a new way of working through new thinking and attitude to work. For this, corporate culture should focus providing value for the consumer and continuous improvement.Conclusions. The concept of continuous improvement and lean production based on a constant desire to eliminate all types of losses and a technology for steadily reducing costs; active involvement of employees in the transformation of the enterprise in the context of limited resources and strong competition — all this will increase the competitiveness and stability of the shipbuilding enterprise in the market.

The use of Lean Manufacturing principles to improve production processes by better designing of assembly cells

One of the pillars of Lean Management is continuous improvement of production processes. Thus, while designing new workstations, it is worth taking into account the requirements resulting from this management philosophy. The question remains how to formulate these requirements, at what design stage to use them and how to do it. A very important aspect of work stations’ design is their ergonomics. Considering the ergonomics of a workplace, we should adapt it to the human anatomical and psycho-physical capabilities. The use of takt time to determine the production capacity of the assembly cell makes it easier to organize tooling, working hours and other factors necessary for effective production. After determining the takt time, it is possible to settle the number of assembly stations we need to achieve the required performance in the analysed time horizon. Another important aspect of Lean Manufacturing is enabling continuous flow of materials between successive production processes. Continuous flow at the assembly stage is ensured by the layout of work stations in accordance with the order of technological operations and thoughtful arrangement of production equipment. This will facilitate further acceleration of production orders, elimination of activities that do not add value, and reduction of labour consumption in the assembly process. In accordance with the aforementioned Lean Management recommendations, a conceptual design of an assembly cell for an example product from the electronics industry was developed. In the case of the analysed product, the idea to ensure continuous flow was to build the assembly cell at the stage when the product design was completed and its trial series produced.

A methodology for identifying cleaner production options to reduce carbon emission in the manufacturing industry

While industries are familiar with environmental management systems for continuous improvement of production processes and products, there are various green-concept-oriented methods that can address environmental concerns significantly. This work focused on adaptation of cleaner production strategy for enhancing environmental management systems. Specifically, this work developed self-implementable methodology that systematically leads to identification of cleaner production options to improve environmental performance and efficiency of manufacturing industry. The developed methodology aims at preventing or reducing carbon emission from production processes and activities. The proposed methodology comprises three steps. In step 1, the sources of carbon emission from the manufacturing industry are identified through materials and energy consumption and waste generation. In step 2, the fate of the sources of carbon emission is determined. The sources are to be prevented or reduced. In step 3, cleaner production options are generated. Cleaner production options include modification of key operating parameters in manufacturing processes, such as temperature, pressure and time; implementation of housekeeping practices; modification of production process; substitution of greener materials; adaptation of new technologies; training to workers and 3R (reuse, recover, recycle). The options are generated with investigative questions. A food manufacturing industry was selected as a case study to demonstrate the practicality of using the developed methodology to generate cleaner production options. A total of 15 specific cleaner production options were identified for the studied premise using the methodology proposed demonstrating the practicality of the developed methodology.

Personalisation of production in the era of Industry 4.0 as a challenge for inventory management in small and medium-sized production enterprises

Industry 4.0 is the result of the development of cyber-physical generation systems as a part of the fourth industrial revolution. Industry 4.0 sets new areas for change in the sphere of production and management but also influences various aspects of society. Industry 4.0 is focused on continuous improvement of production processes. This is a turnaround in the production control methodology, as the growing expectations of customers in the modern market cause, along with the increase in production efficiency, customisation of the product. In this trend, the customer decides about the product, personalising it as much as possible and in the best possible way. These are new challenges in the field of inventory management. The article aims to present a method of calculating the optimal amount of the cost of a rotating stock in a production enterprise with an unevenly distributed demand, which is the case with personalised orders.

Framework for continuous improvement of production processes

This research introduces a new approach of using Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology. This approach integrates various tools and methods into a single framework, which consists of five steps. In the Define step, problems and main Key Performance Indicators (KPIs) are identified. In the Measure step, the modified Failure Classifier (FC), i.e. DOE-NE-STD-1004-92 is applied, which enables to specify the types of failures for each operation during the production process. Also, Failure Mode and Effect Analysis (FMEA) is used to measure the weight of failures by calculating the Risk Priority Number (RPN) value. In order to indicate the quality level of process/product the Process/Product Sigma Performance Level (PSPL) is calculated based on the FMEA results. Using the RPN values from FMEA the variability of process by failures, operations and work centres are observed. In addition, costs of the components are calculated, which enable to measure the impact of failures on the final product cost. A new method of analysis is introduced, in which various charts created in the Measure step are compared. Analysis step facilitates the subsequent Improve and Control steps, where appropriate changes in the manufacturing process are implemented and sustained. The objective of the new framework is to perform continuous improvement of production processes in the way that enables engineers to discover the critical problems that have financial impact on the final product. This framework provides new ways of monitoring and eliminating failures for production processes continuous improvement, by focusing on the KPIs important for business success. In this paper, the background and the key concepts of Six Sigma are described and the proposed Six Sigma DMAIC framework is explained. The implementation of this framework is verified by computational experiment followed by conclusion section.DOI: http://dx.doi.org/10.5755/j01.ee.26.2.6969

Framework for Continuous Improvement of Production Processes and Product Throughput

This paper introduces a new framework that allows continuous improvement for the reliability of production process and product throughput. The new framework allows engineers with less effort to define and measure failures of production processes, also enable to analyse these failures. It can be done by identifying the most critical operations in the process that influence on Key Performance Indicator (KPI) such as throughput of that process. Based on the received results, engineer can apply corrective actions and perform continuous improvement by performing daily monitoring of production processes. Current paper involves a basic concept of improvement methodology that followed by a framework development and its description, moreover, a case study regarding this research is under consideration to implement the framework and visualize the results. The framework allows the company decrease production lead time and increase product throughput KPI with less expenditures. This new framework also integrates various tools and methods like Six Sigma DMAIC, FMEA, TOC, FC, swim-line diagram.

Melhoria contínua dos processos e combate ao desperdício através da ferramenta qfd: o caso da metalúrgica

Este trabalho propõe a utilização do QFD para melhoria contínua dos processos produtivos e combate ao desperdício. Para coletar as informações empregou-se a observação simples e um questionário com perguntas fechadas aplicado aos colaboradores, representando 88,75% da população que atua nos processos produtivos de uma indústria do setor metal mecânico, localizada no Estado do Rio Grande do Sul. O QFD é um método eficiente de planejamento da qualidade, pelo fato de fornecer um diagnóstico da realidade que subsidia a definição de ações de melhoria com vistas ao combate do desperdício. Ações foram definidas proporcionando melhoria da comunicação entre os setores, possibilitando o fornecimento de produtos com especificações que atendem aos requisitos dos clientes, nos prazos e quantidades corretas, a um custo mínimo e plena satisfação das pessoas envolvidas com a empresa. A implementação dessas ações reduz os desperdícios, minimiza o trabalho adicional, maximiza o trabalho efetivo e aumenta a lucratividade.

Integration of neurocomputing and system simulation for modeling continuous improvement systems in manufacturing

The use of a neural network embedded in a larger general-purpose simulation system (GPSS) simulation used to model continuous improvement systems (CIS) policies in a factory setting is described. The neural network is used to accelerate the identification of an effective CIS policy by providing a more realistic simulation framework. The interface between general simulation theory and neural network simulation is examined. Neural networks, when embedded in larger general-purpose simulations, are found to offer the potential for improving on the capabilities of those simulations, in particular manufacturing simulations for continuous improvement of production processes.