Вирішення задачі мінімізації ризиків імпортозаміщення в процесі заводського ремонту військової авіаційної техніки в умовах особливого періоду

Electrical infrastructure equipment in the petrochemical and/or oil and gas industry in North America is generally 40 or more years old. The life and reliability of electrical equipment in this age range can be compromised due to operating conditions such as exposure to moisture and chemicals, loading, temperature, vibration, and mechanical stress over the life of the equipment. Electrical equipment operating and life cycle philosophies tend to vary from age based replacement to run-to-failure. This results in an ad-hoc approach for determining the appropriate time for equipment replacements or major repairs. Limited resources, funding, and other competing projects exacerbate the issue. An operating and life cycle management philosophy using preventive and predictive maintenance results to prioritize equipment replacements and/or improvement will help optimize how to determine when equipment repair or replacement is justified. This paper will describe a systematic risk based approach of prioritizing electrical equipment replacement and repair projects to improve electrical reliability and safety. The approach uses probability and consequence techniques for equipment repair or replacement.

In this paper a notion termed nonstationary fuzzy sets is introduced and the concept of random perturbations that can be used for generating these nonstationary fuzzy sets is also presented. A case study was carried out to investigate the relationship between the performance of nonstationary fuzzy logic systems and interval type-2 fuzzy logic systems. It can be observed that in case of centre variation, the lower-upper boundaries of outputs predicted by nonstationary systems are slightly narrower than those from the corresponding interval type-2 systems. On the other hand, in case of width variation, the lower-upper boundaries of outputs predicted by nonstationary systems are slightly wider than those from the type-2 systems. Moreover, an interesting observation is that the secondary membership function of the type-2 sets corresponding to nonstationary fuzzy sets generated using normally distributed perturbations are nonuniform. In contrast to noninterval type-2 sets, this does not affect the inference process of the nonstationary sets. In this sense, the use of nonstationary fuzzy sets may enable approximations to be made of general type-2 fuzzy inferencing

In addition to equipment maintenance decisions, spare parts ordering decisions from different suppliers play a key role in reducing related costs (e.g., maintenance, inventory and ordering costs). Since suppliers may use different production technologies and materials, spare parts (or products) from different suppliers can be different in quality. Nevertheless, in recent studies, the quality of spare parts is rarely considered to incorporate both equipment maintenance and spare parts ordering. In this paper, we investigate the joint optimization of condition-based maintenance and spare parts provisioning policy under two suppliers with different product quality. We formulate a sequential-decision problem with a Markov decision process and consequently obtain an optimal maintenance and ordering policy by an exact value iteration algorithm. To improve computation efficiency, based on the principle of sequential optimization, we develop heuristic methods. Extensive numerical experiments are conducted to assess the overall performance of the developed heuristic methods. Compared to the optimal method, results showed that the average cost gap is about 2% and computation time is reduced by 94% on average under the proposed heuristic method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the observation that automobile industries tried to integrate emergency suppliers from which spare parts have different quality into maintenance schedules to avoid stockout and reduce equipment failure during the Covid-19 pandemic. Specifically, the article focuses on balancing the trade-offs between condition-based maintenance and inventory management from two suppliers with different lead times and spare parts quality for multi-unit systems. On the one hand, effective maintenance scheduling relies on spare parts for replacement to ensure the stability of production. On the other hand, inventory management needs to select the supplier with appropriate lead time and product quality to reduce the ordering cost and avoid stockout based on the degradation states of equipment. The joint optimization of these two aspects serves to reduce the total maintenance and ordering cost. Nevertheless, most existing research aims to optimize them separately. In this paper, we formulate the joint decision problem considering the two aspects based on a Markov decision process. We obtain an optimal maintenance and ordering policy by an exact value iteration algorithm and present heuristics to improve the computation efficiency when the system contains multiple machines. Practitioners can implement the proposed methodology to make condition-based maintenance and inventory management when spare parts with different qualities are ordered from two suppliers. To balance cost and computational efficiency, it is suggested to implement the optimal policy by an exact value iteration algorithm when the number of machines is small in the system and use the heuristic methods when the number of machines is large (i.e., usually larger than 3).

The paper aims to bridge the gap between the theoretical potential of Additive Manufacturing (AM) and its practical implementation for spare parts management, offering a potential contribution to practitioners in emerging countries. The paper proposes a structured framework for adopting Additive Manufacturing (AM) in spare parts supply chains by first evaluating suitable production methods and then proposing three distinct integration strategies at the enterprise, supplier, and corporate levels.The research adopts a Systematic Literature Review (SLR) using the databases Google Scholar, ScienceDirect, and Scopus. The literature relates to AM, spare parts production, and Supply Chain Management (SCM) challenges. Based on the reviewed papers, suitable AM technologies for spare parts production were identified and analysed to outline their potential across multiple characteristics. After that, papers on SCM were reviewed to develop a simplified framework for implementing spare parts using AM across three distinct integration strategies. The framework is tailored to respond to the needs of practitioners in emerging economies.The results demonstrate that suitable AM technologies should be selected for spare parts production, based on several criteria, including mechanical characteristics, materials, and cost. The paper confirms that implementing spare parts production using AM is feasible in emerging countries by adapting one of the three practical frameworks to each company's situation. Additional recommendations are provided to enable the combination of AM technologies with a conventional manufacturing system.The study is primarily limited by its reliance on theoretical literature rather than empirical studies, which may limit the direct applicability of the findings in industry. Nonetheless, it focused approach provides a foundational framework that researchers and practitioners can adapt and test in industrial contexts, especially in emerging economies.The research provides researchers and practitioners in emerging economies with a direct, actionable tool for selecting the AM technology to produce spare parts. It offers a clear roadmap to strategically integrate AM into their production within a conventional manufacturing system.The paper compares AM methods for the production of spare parts and presents preliminary insight into their SCM. The finding aims to enhance research on AM and its integration with conventional manufacturing systems in emerging countries.

The article summarizes results of monitoring the processes and problems of import substitution in Russian industry, held by Institute for Economic Policy and based on surveys of the directors of industrial enterprises in 2014-2016. Enterprises' managers were interviewed not as producers of Russian goods, but as consumers of import machinery, raw materials and fabrics. Predevaluation estimation of Russian industry's readiness to switch to the Russian substitutes of import showed significant critical dependence on import of domestic enterprises, which had been confirmed also in December of 2014. Lack of production of machinery, raw materials and fabrics similar to foreign, on the territory of Russia was and remains the main problem in import substitution both in the beginning of 2015 and at the end of 2016. Low quality of already produced substitutes also constrains broad import substitution in industrial enterprises' purchases. Insufficient volume of Russian industryoutput comes on the last place in the rating of restrictions limiting import substitution, according to enterprises. Nevertheless, Russian industry is able to refuse from import and switch to Russian analogs, primarily in terms of machinery and equipment. However, the rate of maintained import had always exceeded the scale of import substitution in 2015-2016. Exchange rate strengthening and adaptation to new economic conditions reduced the scale of the real import substitution and industrial plans in this area.

Technical means of intelligence (hereinafter – TMI) are widely used in all spheres of intelligence activity. Their element base and schematic solutions are continuously improved in the direction of automating the execution of technological operations. This leads to an increase in the number of elements in the product, which in turn does not contribute increasing reliability indicators. Therefore, the issue of restoring performance in the event of failures of TMI is quite relevant, since the time of technical diagnosis takes up to 80 percent of the repair time. The authors have been working for many years in the field of technical diagnostics of complex objects and systems, which differ in purpose, schematic and constructive construction, and requirements for recovery time. At the same time, it is important to develop high-quality diagnostic support for repairs, taking into account the specifics of the specific object of diagnosis, as well as the conditions for restoring performance. Some sources consider the use of some features of the object of diagnosis during the development of their diagnostic support, but there is no general approach to this. Therefore, the article proposes the use of all features of the object of diagnosis to improve the quality of their diagnostic support. This makes it possible to ensure the necessary quality of restoration of the functionality of the object of diagnosis with minimal costs. It is advisable to use the proposed proposals during the improvement of the existing diagnostic support and its development for promising technical means of intelligence. In the future, the authors plan to conduct research in the direction of increasing the efficiency of diagnosing discrete objects, as well as with accident and combat damage in the presence of multiple defects.

Preface6th annual 2018 International Conference on Material Science and Environmental Engineering [MSEE 2018] was held on November 23rd-25th, 2018, Chongqing, China. MSEE2018 aims to bring researchers, engineers, and students to the areas of Material Science and Environmental Engineering. MSEE2018 features unique mixed topics of Material Science and Advanced Materials, Material Engineering and Application, Environmental Protection and Sustainable Development, Renewable Energy and Building Energy Saving, Environmental Science and Engineering.We received over 275 submissions from various parts of the world. The Technical Program Committee worked very hard to have all manuscripts reviewed before the review deadline. All the accepted papers have been submitted to strict peer-review by 2-4 referees, and selected based on originality, significance and clarity for the purpose of the conference. The conference program is extremely rich, profound and featuring high-impact presentations of selected papers and additional late-breaking contributions. We sincerely hope that the conference would not only show the participants a broad overview of the latest research results on related fields, but also provide them with a significant platform for academic connection and exchange. There is one keynote speaker and five invited sessions. The keynote speakers are internationally recognized leading experts in their research fields, who have demonstrated outstanding proficiency and have achieved distinction in their profession. The proceedings would be published by IOP Conference Series: Materials Science and Engineering (MSE).We would like to express our sincere gratitude to all the members of Technical Program Committee and organizers for their enthusiasm, time, and expertise. Our deep thanks also go to many volunteers and staffs for the long hours and hard work they have generously given to MSEE2018. The last but not least, we would like to thank all the authors, speaker and participants for their great contributions to the success of MSEE2018.MSEE2018 Organizing CommitteeProf. Ke WangEast China University of Technology, China

Development and Production Costs Estimating for Aviation Equipment Based on Uncertainty Design

The article compares the different production technologies: traditional and modern. There has been increasing currently the need for successful competitive struggle of customized technology example of which is Lean Production – a system of principles, concepts and tools, developed by the japanese company Toyota, the purpose of which is the elimination of waste. The reasons of departure from the technology of mass production. The key concept of the Lean approach – the «value» of the product defined by the end user. «Utility» create a technological operation in which there is a change in the geometric shape, the addition of physical or chemical properties. From the point of view of Lean Production, only these costs can be included by the manufacturer in the price, and everything else does not add value for the customer, and therefore should be eliminated. The article provides a classification of the various types of losses. One of the objectives of the author of this article is to list and describe problems of implementation of Lean Production at domestic enterprises. The first of them is a high proportion of costs that do not add value, which reduction is only possible using the global transformation of the operating system of the enterprise, changes to organizational structure and management system. The second is mentality, which creates additional difficulties during implementation. Third is the need for a short time to develop its own production system to catch up with western companies for decades implementing this approach. In this regard, the necessity of understanding technology Lean Production of the russian scientific environment, development of practical manuals and guidelines for implementation in domestic enterprises, etc.

Maintenance strategies are designed and implemented in order to reduce the frequency and duration of service interruptions, while satisfying constraints on budget, productivity, space, etc. A maintenance strategy is defined as the set of actions pertaining to maintaining or restoring a system in a specified state or in a state of readiness to accomplish a certain task. The main scientific contributions dealing with maintenance policies generally address the three following issues in a separate or combined way: the choice and the sequence of actions defining each strategy, the costs and durations of these actions, and the equipment lifetime and repair distributions. For many companies, the expenses incurred for keeping spare parts until they are used increase significantly the cost of their finished goods. Huge costs related to the inventory management of those parts have triggered studies on the provisioning and management decisions made in the process of acquiring and holding spare parts stocks.

Are Foils the Future of Anodes?

It is well-known that reliability of equipment is the most important of all performance to all equipments. In order to make the equipments which include mechanical equipments, electrical equipments and so on work normally, reliability theory FMECA is applied in an aviation equipment to study its reliability and improve operational reliability of the product. Through its reliability mathematical model, average of operational time is predicted based on calculating failure probability of all electrical components. According to the process of FMECA, all kinds of the failure mode, reasons, effects and criticality of the products can be determined completely. By comparing these criticality data as shown, the paper analyses adopted method by that the contents, accents and operating process of maintenance may be instituted finally. FMECA-based method for reliability study of the equipment and the equipment maintenance perform well. The results indicate that application of FMECA method can analyze reliability in detail and improve operational reliability of the equipment. Therefore this will supply theoretical bases and concrete measures of maintenance of the products to improve operational reliability of products. FMECA can be feasible and effective for improving operational reliability of all equipments.

Problem statement. A programmable logic controller is a key tool for automating technological processes and production in the energy sector, transport infrastructure, industry, agriculture, housing and communal services. In the article the development of a programmable logic controller based entirely on domestic hardware components is considered.Objective. To offer circuit solutions that allow developing a programmable logic controller using domestic hardware components exclusively.Results. Schematic solutions and achieved technical parameters of programmable logic controller are presented. The controller was developed entirely on the domestic element base at the enterprise JSC “Avangard” (St. Petersburg). The parameters of the controller correspond to the main indicators of the technical assignment for its development during the implementation of the Comprehensive Project under the State Program of the Ministry of Industry and Trade of the Russian Federation.Practical implications. Production of programmable logic controllers based on the domestic hardware components exclusively solves the national goal of import substitution of devices of this class.

The automotive sector has been very progressive to experiment with additive manufacturing (AM) and early started to adopt it for rapid prototyping. Nonetheless, until the present day the integration of AM in the production of car parts, such as spare parts, proved to be difficult. Spare parts are generally characterized by demand uncertainty. Therefore they require high inventory levels to guarantee short lead times and high service levels for maintenance, repair and overhaul firms. The deployment of AM technologies in spare parts production has the potential to overcome these supply chain-related challenges. This research conceptually investigates the effects of AM in the automotive spare parts business for different supply chain scenarios. As a main contribution of this paper, four scenarios are developed and systematically analyzed regarding their suitability and implications for an AM implementation in the automotive spare parts supply chain.

Subject Russian import substitution for machinery and equipment. Significance In response to sectoral sanctions imposed by the United States and EU since 2014, the Russian government has pursued an economy-wide import substitution programme to encourage local development and production of technologies. The policy will be sustained because no end to Western sanctions is in sight, and it fits the government's broader aim of encouraging competitive hi-tech industries and -- for political as well as economic reasons -- making Russia less dependent on more advanced economies as well as on its own oil and gas sector. Impacts The government's commitment to fiscal discipline will restrict funding to projects with verifiable future payback. Spare capacity in the hi-tech defence sector will be turned towards non-military production, probably beyond 2020. Import substitution necessitated by Russia's 2014 ban on certain food imports have spurred crop diversification and growth in farming.