Management Of Manufacturing Systems Research Articles

Motivation as key factor of deploying lean technologies in medical institutions (an analytic review)

Aim. To assess the importance, role, methods and conditions for creating and sustaining positive motivation of medical personnel in deploying a modern management system based on lean production to optimise the production flow in medical institutions, improve quality, availability and efficiency of public medical care.Materials and methods. The authors employed historical, bibliometric and statistical methods to analyse domestic and foreign scientific archives on lean production, motivation and motivational risks as key factors in implementing lean technologies in medical institutions.Results. Implementation of lean production (LP) as a manufacturing management system is among key conditions for creating a new model of the medical institution. Principles of LP are applied at three interfaces: with patients, personnel and resources. Positive motivation of employees is prerequisite for accomplishing a project, which requires supervisors to know and leverage the basics of motivational management. Creation of a motivating environment for various categories of employees in developing a LP system requires taking into account the type and management culture level of a medical institution.Conclusion. In order to create and sustain motivation for realising creative potential of the team, it is necessary to account for the motivation risks, develop and implement a motivation system differentially by employee categories and project stages. Effective motivational measures are necessarily based on a system of material and non-material incentives with clear and achievable criteria, amounts and forms valued by employees and rooted in medical and economic feedback of implementing the LP principles.

Multi-agent deep reinforcement learning based demand response for discrete manufacturing systems energy management

With advances in smart grid technologies, demand response has played a major role in improving the reliability of grids and reduce the cost for customers. Implementing the demand response scheme for industry is more necessary than for other sectors, because its energy consumption is often considered the largest. This paper proposes a multi-agent deep reinforcement learning based demand response scheme for energy management of discrete manufacturing systems. In this regard, the industrial manufacturing system is initially formulated as a partially-observable Markov game; then, a multi-agent deep deterministic policy gradient algorithm is adopted to obtain the optimal schedule for different machines. A typical lithium-ion battery assembly manufacturing system is used to demonstrate the effectiveness of the proposed scheme. Simulation results show that the presented demand response algorithm can minimize electricity costs and maintain production tasks, as compared to a benchmark without demand response. Moreover, the performance of the multi-agent deep reinforcement learning approach against a mathematical model method is investigated.

Complex networks of material flow in manufacturing and logistics: Modeling, analysis, and prediction using stochastic block models

Modeling complex systems as networks of interacting elements has gained increased attention in recent years. So far, network modeling in manufacturing and logistics has often focused on the description of system properties. In the data-driven world of smart manufacturing, creating material flow network models becomes a lot easier due to the ubiquitous availability of shop floor and transportation data. At the same time, these highly flexible and continuously changing smart manufacturing systems become less predictive and thus less controllable. This article investigates how the stochastic block model (SBM), a network model with a stochastic description of interconnections, can be applied to model and predict material flows in manufacturing systems. We show how to utilize its properties to forecast the dynamic development of the structure of such systems. The complete process from network modeling using material flow data to the prediction of the future development of the network is demonstrated. Different SBM variants are tested using six company data sets and evaluated in competition with classical machine learning methods for prediction. Our results show that selected SBM variants achieve the best performance in prediction in most scenarios and thus have the potential to play an important role in the management of future dynamic manufacturing systems.

THE APPROACH OF SOFT SYSTEMS METHODOLOGY FOR SYSTEM ONLINE MANAGEMENT CONSULTANT CONSTRUCTION

Consultant as a service provider konstrukusi in order to realize its goal to ensure public safety and create a comfort environment of the construction need to organize a system of internal governance of the company. Governance is translated into the stages of the stages in the implementation of Construction Services. Soft Systems Methodology is the methodology suitable to assist the consultant planner. This methodology can explain their purpose and then designing the system of human activity to achieve these goals. The stages that exist in the methodology of SSM consists of 7 stages that starts from the verification problem situation that is not structured through the design of the system of human activity which are expected to help improve the situation. Think the system is a field transdisiplin that appears as a response to the limitations of a technical approach in the process of reduction to solve a certain problem which in this case is attempted to be applied through the SSM as a method in the application of the online management system (OMS) consultant planner construction. Using the approach of Soft Systems Methodology, manufacturing management system online (CSO) will more fully describe the problems that occurred previously.

The smart technologies application for the product life-cycle management in modern manufacturing systems

Perspective directions of development of information technologies in the field of improvement of programs of universal artificial intelligence for tasks of the organization of production are Considered. Modern trends of application in production are considered and advantages to companies are analyzed. The concept of building a production process using smart technologies and other artificial intelligence approaches is proposed.

Drivers in Adoption of Advanced Manufacturing Management System for Environmental Sustainability

Competitiveness is one of the most important aspects of business in the current business environment. Adoption of Advanced Manufacturing Management System (AMMS) helps companies in improving competitiveness. Also, the growth of manufacturing sector is not possible without adoption of AMMS. India is a country looking to get multidimensional benefits from growth of manufacturing sector. But Indian manufacturing sector is suffering from resource crunch. It is not easy task to adopt AMMS because of limited availability of resources. Since, AMMS are linked with environmental sustainability also; this paper finds various drivers in adoption of AMMS for environmental sustainable manufacturing. These drivers are placed in priority matrix which is helpful to companies in formulation of strategy regarding environmental sustainability. Using literature review and expert discussions, 31 drivers are identified in adoption of AMMS for environmental sustainable manufacturing. A group of experts having experience in academic as well as industrial experience ranked drivers and placed them in a priority matrix. With known set of impactful drivers, it is easy to choose appropriate strategy for effective yielding of environmental sustainability for any company. This study is focused only on environmental aspect of sustainability.

Quality Management in Manufacturing and Technological Systems

This article discusses the peculiar features of quality management in modern manufacturing and technological systems with consideration for risk-based thinking, in particular, which characterizes quality as a measurable and estimable factor, its indices, existing major categories of quality management, how and when they are applied, as well as their distinctive features.

Design and management of digital manufacturing and assembly systems in the Industry 4.0 era

The advances in Industry 4.0 provide both challenges and opportunities for digital manufacturing and assembly systems. This paper first addresses the state-of-the-art readiness for Industry 4.0 concerning assembly and manufacturing systems through a literature review of the relevant papers recently published. Then it assesses the challenges faced nowadays by assembly and manufacturing systems. Third, it focuses on the most promising future developments and evolution of such production systems as well as their digitalisation. Finally, this manuscript illustrates the content of the papers selected for this special issue. Through the study presented in this special issue, valuable contributions to both theory and application in this area have been achieved, and a useful reference for future research is given.

FORMATION AND CONTROL OF THE QUALITY OF FOOD AND FEEDS: FROM THE BASIC TECHNOLOGIES TO THE HUMAN FACTOR

Today, the European vector of our country’s development and the strategy of economic partnership with the EU pose certain challenges for our state. Signing the EU Association Agreement made an important impact on the changes in Ukrainian legislation concerning harmonization of laws and rules in economics. Providing the proper quality of agricultural products remains an important task. It requires improving the organizational and legal support in changing accents in legal regulation: giving manufacturers more freedom in economic issues instead of administering directly. The above-mentioned Agreement gave a good boost to create the State Service of Ukraine for Food Safety and Consumer Protection, which, in turn allowed merging three state organizations to start monitoring food safety and quality “from field to fork.” Especially important are the Requirements to the Development, Introduction, and Usage of Standing Procedures based on the HACCP system principles. Today, HACCP-based certification of standing procedures is not obligatory, unlike the presence of Prerequisite Programmes of HACCP, which is obligatory. A Prerequisite Programme must cover 13 processes: from planning the manufacturing, auxiliary, and staff facilities in order to avoid cross-contamination to marking finished products. A number of requirements must be met by each of these processes in particular. The authors of this article have analysed the legislation changes and the latest publications about a number of Ukrainian food enterprises that have introduced the HACCP principles. This analysis has allowed concluding that in these enterprises, this process has caused some changes in their manufacturing technologies and management systems. Groups of factors influencing the products’ quality have been outlined. The importance of the human element at various stages of quality formation and control has been emphasized. The existing systems of quality and safety management in food industries have been analysed in detail.

Formal Tools for Management of Manufacturing Systems: A Multi Agents System Approach

To overcome the consequences of the 2008 crisis on the real sector, especially manufacturing, Industry 4.0 gives guidelines to drive production by emphasizing technological innovations, such as industrial internet, cloud manufacturing, etc. The proposed paper focuses on cognitive manufacturing within the framework of the emergent synthesis paradigm. Specifically, the structuring process by which the manufacturing assets are organized to provide the finished goods is analyzed. The study is carried out by considering the analogies between manufacturing and other inventive processes supported by formal tools such as formal languages, semantic webs, and multi agent system.

Throughput Estimation Model of Cluster Tool in Semiconductor Manufacturing

Semiconductor manufacturing management system was developed and grown up over the past decades. In order to increase the product yield and enhance the production productivity, cluster tools became the main stream in modern wafer fabrication factories which occupies over 50% of production equipment. Generally, cluster tools are integrated by several components including robots, vacuum chambers (Load locks) and single-wafer process chambers in a module and can be treated as a small factory. The throughput estimation before recipe release is very difficult. However, it is necessary and important for the planning activity. In this work, a throughput estimation model for cluster tools is proposed. The Multiple Regression Analysis is applied to develop a set of throughput estimation equations. A simulation model of cluster equipment including 3 single-wafer process chambers are built to get the historical throughput data for the regression analysis. From the Multiple Regression Analysis, it reveals that different numbers of recipes processed in the same time have to develop different regression model. The major factors in the regression model include numbers of load ports and process time of each recipe. Furthermore, a set of recipes are used to test the accuracy of estimation. Based on the testing results, they revealed that the MAPE is under 3% and the estimation model is accepted in practice to forecast the throughput of recipes for the planning activities.

Динамические модели управления научно-производственными системами

dynamic models, research and manufacturing systems, capacity, conveyor systems, uncertainty, marginal profitabilityThe paper considers dynamic models of resource management in manufacturing systems. Such system operating benefits largely depend on the rational use of resources such as the production apparatus, human resources, borrowed and own funds. The importance of scientific and practical problem of management manifests itself in the aspects of management automation based on the development of mathematical models optimizing the activity in accordance with the selected criteria and allowing obtaining well-founded decisions for the use of production and financial resources. The manufac-turing company management system based on the principles of conveyor processing applications is considered (applications in the broad sense are materials, work in progress, data, documents of computing and information centers, etc.). The equations describing the operation of conveyor systems are presented. The methods of resource allocation based on the criterion of maximizing the total volume of processed applications and the criterion of maximizing the marginal income for the policy period are considered. The application frame of these models for interval parameter settings in the conditions of initial data uncertainty with allowance for the attraction of debt financing is investigated. The analysis of stability of solutions is performed by means of economic and mathematical modeling

Dynamic design and management of reconfigurable manufacturing systems

This research proposes an approach to design and to manage Cellular Reconfigurable Manufacturing Systems (CRMSs) from a multi-product and multi-period perspective. The production environment consists of multiple cells of machines equipped with Reconfigurable Machine Tools (RMTs) made of basic and auxiliary custom modules to perform specific tasks. The approach acts into two steps; the former is the machine cell design phase, assigning machines to cells, the latter is the cell loading phase, assigning modules to each machine and cell. The goal is to guarantee the economic sustainability of the manufacturing system by exploring how to best balance the part flow among machines already equipped with the required modules and the effort to install the necessary modules on the machine on which the part is located.

Development of an Educational Program Combining an Educational System for University Students with an Educational System for Engineers Working at Actual Companies to Educate an Administrator for Manufacturing System

An administrator of manufacturing factory requires knowledge of manufacturing management to enhance productivity and quality of products. In recent production environment, the administrator requires knowledge of management of manufacturing system including product planning and product design to continue productivity of factory. In this study, we call this administrator as "an administrator of manufacturing system" and we construct educational program to study the knowledge of manufacturing management. This program includes kaizen activity in actual factories by a group of university students and working engineers. In this paper, we explain characteristics of the developed educational program and case study in actual factory.

Establishment of Cosmetic Raw Material Weighing and Bulk Manufacturing Management System Using Bar Code, QR Code and Database

Establishment of Cosmetic Raw Material Weighing and Bulk Manufacturing Management System Using Bar Code, QR Code and Database

푸드테크 관련 한국과 일본의 특허 등록 현황

This study analyzed the current status of registered patents related to food tech in Korea and Japan. Using the patent information search services of Korean and Japanese Patent Offices, patents registered during the past 10 years from January 1, 2005 to December 31, 2015 were searched with the following key words/phrases: “food or meal or diet” and “program or information system”. A total of 669 patents (539 for Korea and 130 for Japan) were finally selected and analyzed. Based on Porter's value chain theory, the patents were categorized into three dimensions related to “manufacturing/processing/ distribution”, “sales & marketing”, and “consumer support”. The results showed that in Korea, 41.7% of the total patents were related to sales & marketing followed by consumer support (37.3%) and manufacturing/processing/distribution (21.0%). In Japan, patents related to consumer support accounted for 56.2% followed by manufacturing/processing/distribution (32.3%), and sales & marketing (11.5%). In the area of manufacturing/processing/distribution, “food quality management system” in Korea, and “food manufacturing and processing management system” and “food safety control and hazard analysis system” in Japan tended to show a significantly higher proportion of patents registered (p<.05). Under sales & marketing, patents in the categories of “food purchase and delivery service system” in Korea and “restaurant information sharing system” in Japan tended to be more frequently registered (p<.05). Finally, in the area of consumer support, “kitchen facility and cooking device control system” in Korea and “menu and nutrition management system” in Japan tended to account for a significantly higher proportion of patents registered (p<.001). The results are expected to provide useful insights into the development of new patents and markets for food tech in the future.

Joint Optimization of Process Flow and Scheduling in Service-Oriented Manufacturing Systems.

Customer-oriented management of manufacturing systems is crucial in service-oriented production and product service systems. This paper develops the selection of dispatching rules in combination with alternative process flow designs and demand mix, for a maintenance, repair and overhaul center (MRO) of turbo shaft engines, both for complete engines and engine modules. After an initial systematic screening of priority dispatching rules, the design of experiments and discrete-event simulation allows a quantitative analysis of the better rules for the alternative process flows with internal and service metrics. Next, the design of experiments with analysis of variance and the Taguchi approach enables a search for the optimal combination of process flow and dispatching rules. The consideration of extra costs for overdue work orders into the costing breakdown provides a quantitative evaluation of the optimum range of load for the facility. This facilitates the discussion of the significant trade-offs of cost, service, and flexibility in the production system and the operational management alternatives for decision-making.

Creation of a lean management system at an enterprise of the defense industry complex

Specifics of the implementation of lean manufacturing management system (SMPS) tools at the domestic enterprises of the defense-industrial complex, who take efforts towards the increase of the economic efficiency of their production and business operations, have been reviewed. The applied SMPS tools introduced or being introduced by business entities have been analyzed. Approaches to planning and content of the stages of SMPS tools implementation at the defense industry enterprises have been formulated.

Simulation Tool for Assessing the Performance of a Flexible Manufacturing System

The flexible manufacturing system (FMS) is as complex whole, raises concerns regarding the configuration and dimensioning, as well as on the conditions for implementation. The scientific researches in this paper, are directed towards the study and analysis of flexible manufacturing systems, in order to know their behaviour and performances as well, and if possible, even before their physical realization, and to establish the scientific basis for sizing, configuration and simulation patterns of flexile manufacturing systems. The ARENA simulation software can describe the complex interactions between resources and processes that take place within a FMS, a system of discrete events. In the simulation phase, evaluation of performance criteria allows the introduction of planning strategies in the use of system resources. After developing these models the verification and validation of the models, confirms their validity. The researches will be also extended in the domain of flexible manufacturing systems management and control in real and virtual environment.

Special Issue on Service Engineering

To solve problems underlying design and manufacturing we often rely on methodologies of computational intelligence such as machine learning, artificial neural networks, fuzzy logic, fuzzy inference systems and smart optimization algorithms. In this Special Issue of the International Journal of Automation Technology, original articles are presented with reference to the engagement of intelligent computation in diverse application areas of design and manufacturing, including manufacturing process monitoring, manufacturing systems management, scheduling, design theory and methodology. The six research papers in this Special Issue propose the use of intelligent computation methodologies to deal with various topics related to manufacturing and design. In particular, the first three papers focus on manufacturing process monitoring with reference to different manufacturing technologies, including tool wear monitoring in drilling of composite materials, sensor monitoring in CNC turning and residual stress prediction in welding. Diverse intelligent approaches such as artificial neural networks and adaptive neuro-fuzzy inference systems are proposed to support manufacturing process monitoring. The fourth paper deals with the manufacturing system level, proposing the employment of a solution algorithm combining metaheuristics and operation simulation for scheduling of production processes. The fifth paper aims at developing tools to guide the manufacturers to manage the technology investment and cost saving target for customer satisfaction based on the application of internet of things. The last paper proposes a methodology to support the introduction of customer requirements in product and service design via a decision support system which exploits artificial intelligence algorithms (machine learning) based on inductive inference, allowing knowledge related to product/service to be mapped, structured and managed to design the service and product semantic model. The editors deeply appreciate all the authors and anonymous reviewers for their effort and excellent work to make this Special Issue unique. We hope that future research on intelligent computation in manufacturing and design will advance manufacturing technology and systems as well as design methodologies.