Operational reliability and quality loss of diversely configurated manufacturing cells with heterogeneous feedstocks

Machine reliability in cellular manufacturing is a challenging engineering problem in the formation and design of manufacturing cells. The heterogeneity of feedstock quality is also common in manufacturing industry. However, so far, no work has been done to investigate the performance of diversely configurated manufacturing cells under the heterogeneous feedstocks. In this paper, considering the actual engineering condition, the uniformly random arrival and the clustered arrival of low-quality feedstocks are proposed and modeled by the homogeneous Poisson process and Hawkes process, respectively. Also, to study the mixed reliability of a machine under the impact of heterogeneous feedstocks, a mixed failure-rate model is constructed by the mixture of exponential and Weibull distributions, and the processing quality is modeled by a non-homogeneous Poisson process with a dynamic intensity function. Then, we achieve a contrastive analysis for operational reliability and quality loss of manufacturing cells with basic serial and parallel configurations under the impact of heterogeneous feedstocks. At last, the designed simulation illustrates the effectiveness of our proposed models, and some results are concluded to provide some guidelines for the design of manufacturing cells.

Effect of Preventive Maintenance on Machine Reliability in a Beverage Packaging Plant

This paper investigates the effect of preventive maintenance on the reliabilities of devices in a bottling plant. Six months of real-time maintenance data were analyzed quantitatively. Based on the breakdown events obtained for each machine, mean time between failure (MTBF), mean time to repair (MTTR), and failure rate (λ) values for individual equipment are calculated. The bottle packer, empty bottle inspector (EBI), and palletizer are identified as the plant's critical machines. A breakdown analysis (BDA) is then performed on the bottle packer and from the failure mode of all the reoccurring problems affecting this machine as a result of ineffective PM. An autonomous maintenance (AM) team is set up as part of establishing an effective PM program to improve the reliabilities of the critical machines that were continually falling. A significant reduction in machine breakdowns is observed after two months of rolling out the AM program. As a result, the reliability of bottle packer increased from 55.30% to 70.80%, while EBI and palletizer increased from 89.20% and 87.20% to 92% and 90.50%, respectively.

Analisa Perbaikan Manajemen Perawatan Dengan Metode Reliability Centered Maintenance Bagian Cnc Wirecut di PT X

PT X is one of the manufacturing companies in Indonesia, which specializes in manufacturing molds and dies which offers products to the internal group and the domestic market. This study discusses the policy analysis of machine repair maintenance management using the RCM (Reliability Centered Maintenance) method approach at the PT X manufacturing company. Some of the problems that occur are sudden engine failure, which will cause over production. One machine that is considered critical is the CNC Wirecut K90 machine. With the application of using RCM it is expected to improve machine reliability through several systematic RCM implementations: system selection and information collection, defining system boundaries, system descriptions and function block diagrams, describing system functions and functional failures, compiling Failure Mode and Effect Analysis (FMEA), composing Logic Tree Analysis (LTA), selection of actions. The new policy set by the Realibility Centered Maintenance (RCM) method consists of 14 failure modes that are resolved by time-directed (CD) and 6 failure modes that are overcome by run to failure (RTF). In the FMEA analysis, there are 4 components that most often fail to function, namely the electrode pin, wire guide, filter and contact fit. The determination of this component is based on the RPN value and data in the field. In the RCM analysis, the electrode pin, wie guide and contact fit components are included in the run to failure (RTF) treatment policy category. Meanwhile, the filter component is in the category of condition direction (CD) maintenance policy with an average failure rate of 29,951 days.

The Use of Predictive Maintenance in the Production Processes

Failures are a problem for every company that causes the plant to stop working and thus incur losses. It is therefore obvious thatcompanies want to eliminate unplanned downtime in the production process. In the wake of the still increasing demands in termsof productivity and safety requirements, cost reduction, the industry is forced to seek the optimum between economic requirementsand an acceptable level of risk in terms of security. Modern factories equipped with computerized processes and extensive diagnostictools often do not use all the information that is collected from the hardware level. It happens that some of the relationshipsbetween events are often overlooked or neglected.The article presents an approach to increasing machine reliability through predictive data analysis. The assumptions of the predictiveand preventive maintenance methods are presented. The threats and possibilities offered by this methodology implemented inthe production process are presented.

Improving the reliability of transport vehicles based on element-by-element analysis

The author considers two approaches to solving the problem of increasing the reliability of machine-building products: on the spot, at the enterprises that operate transport vehicles, via certain modifications of serial products, and at manufacturing sites, during production of subsequent products, via improving the design on the basis of operation data of the analogues. In this case, data collection and processing system should provide reliable data on failures and cases of non-serviceable condition of the machines operating under different conditions; prompt processing of statistical data and presentation of results in the most convenient form; registration and coordination of reliability improvement measures taken by developers, manufacturers and operators. The author analyzes the operation of distribution laws of random variables and the variety of their corresponding calculation systems for the determination of the product's reliability indices in an element-by-element, unit-wise, as well as synthesized form. This approach makes it possible to search for the least reliable elements of a system in order to align the machine's reliability indices. Purpose. Creation of a design system for determining reliability indices in a separate form at the levels of parts, units and for the machine as a whole for identifying its least reliable components for the purpose of their further improvement. Methods. The methodology is based on drawing up a structural chart of machine reliability and a consolidated list of failures that are identified during its operation. The reliability structural scheme includes all the machine elements. A summary cumulative list is compiled further, where data on the operating time of each object are recorded for each failure type. The data samples on the times to failure of a group of homogeneous components are output from the summary cumulative list per each element. Results. The methodology makes it possible to create a system with multiple ratios of reliability indices per components, as well as reduce expenses for service impacts and improve the effectiveness of their transportation work. The present research work contributes to the theory of predicting the reliability of mechanical systems, making it possible to solve important tasks at modernization and design stages.

Reliability and validity of the Hypoxico Everest Summit II altitude generator

The Hypoxico Everest Summit II Altitude Generator produces normobaric hypoxic conditions, which are commonly used in altitude acclimation. Despite being used routinely within applied sport science, this system is yet to be independently validated. Thus, the aim of this study was to explore within- and between-day inter- and intra-machine reliability and validity. Two Hypoxico Everest Summit II Altitude Generators were investigated for six altitude settings in a randomised order (0.5, 3.0, 5.5, 8.0, 10.5, 12.0). Following institutional ethics approval, Hypoxico generated air was sequentially pumped into three Douglas bags, each with a 1-min collection period. Samples were collected on eight occasions, measuring inter- and intra-machine reliability, both within-day (9 AM–2 PM) and between-day (48-h) with samples analysed to determine FiO2 (%) and volume (L·min−1). Coefficient of variation (CV) was calculated for FiO2 and volume for each altitude setting. Mean CV for FiO2 did not exceed 0.42% within-day, 0.49% between-day and 0.81% inter-machine. Volume mean CV did not exceed 0.85% within-day, 0.91% between-day and 1.17% inter-machine. One-sampled t-tests were conducted comparing Hypoxico reference values with collected samples using equivalent FiO2 for each altitude setting with a Bonferroni corrected significance set at p < 0.004. Settings 3.0, 5.5, 8.0, 10.5 and 12.0 all produced significantly different ( p < 0.001) FiO2 concentrations than the reference values stated (−0.51, −0.97, −0.72, +0.41 and +0.40%, respectively). Altitude setting and 1-min volume had an inverse relationship. All settings produced a significantly lower ( p < 0.001) volume by 21.80 to 35.40 L·min−1 as compared to the company’s claim of 126.6 L·min−1. The Hypoxico Everest Summit II produced a reliable and consistent air feed; however, the manufacturer’s reference values demonstrated poor agreement with machine produced FiO2 and volume. Therefore, it is recommended that athletes, practitioners and researchers self-validate the altitude generator post-warm-up using an accurate oxygen sensor for accuracy and safety purposes.

Towards an Industry 4.0-Based Maintenance Approach in the Manufacturing Processes

Maintenance is one of the key application areas of Industry 4.0. Every day, maintenance managers and technicians face the challenge of ensuring maximum machine reliability and availability, while minimizing the utilization of materials consumed by maintenance and repairs. As productivity is pressured to further improve, finding a successful balance between these aspects is becoming increasingly difficult. Therefore, integrating condition-monitoring systems with predictive and prescriptive maintenance principles, a new Industry 4.0-based maintenance can be obtained that enables maintenance engineers to better deal with this challenge. In this context, Maintenance 4.0 expands existing maintenance functions by the integration of Industry 4.0 technologies, like internet of things, cyber physical systems, augmented reality, and 3D printing. This chapter presents the main maintenance areas that are supported and enabled by Industry 4.0 technologies and introduces an Industry 4.0-based predictive maintenance approach for the manufacturing industry.

PERM SCIENTIFIC SCHOOL OF BEARINGS FOUNDED BY PROFESSOR BORIS ALEXANDROVICH IVANOV

The article is devoted to the 100th anniversary of the birth of an outstanding teacher and scientist, professor of the Perm Polytechnic Institute (PPI), now PNRPU, Boris AlexandrovichIvanov, one of the founders of the PPI, a participant in the Great Patriotic War. Boris Alexandrovich graduated from the Kazan Aviation Institute and defended his PhD thesis in 1956; since 1957 he became the head of the department"Machine Parts". Since 1963, the department began to develop a scientific direction-the study of the performance of mainly aircraft rolling bearings. After the All-Union Congress on Machine Reliability held in Perm in 1964, Boris Alexandrovich introduced a section on reliability to the course "Machine Parts". In 1965, on his initiative, a section of reliability and friction units was created at NTO MASHPROM, in which the staff of the department held scientific and technical conferences every two years with the wide participation of specialists from different cities of the country. Scientific and technical seminars with reports were held every quarter, mainly from the enterprises of the city. A brilliant lecturer and educator-teacher of young employees, Boris Alexandrovich paid great attention to improving their pedagogical and scientific qualifications, especially supported the independent work of young people. Under the leadership of Boris Alexandrovich, eleven candidate dissertations were completed and successfully defended, he was confirmed in the title of professor and honored worker of the higher school. So the Perm School of Bearing Workers, well-known in the country, was created. Boris Alexandrovich has always remained in the memory of grateful students.

Coordinated optimization of production scheduling and maintenance activities with machine reliability deterioration

<p style='text-indent:20px;'>In this paper, we investigate a coordinated optimization problem of production and maintenance where the machine reliability decreases with the use of the machine. Lower reliability means the machine is more likely to fail during the production stage. In the event of a machine failure, corrective maintenance (CM) of the machine is required, and the CM of the machine will cause a certain cost. Preventive maintenance (PM) can improve machine reliability and reduce machine failures during the production stage, but it will also cause a certain cost. To minimize the total maintenance cost, we must determine an appropriate PM plan to balance these two types of maintenance. In addition, the tardiness cost of jobs is also considered, which is affected not only by the processing sequence of jobs but also by the PM decision. The objective is to find the optimal job processing sequence and the optimal PM plan to minimize the total expected cost. To solve the proposed problem, an improved grey wolf optimizer (IGWO) algorithm is proposed. Experimental results show that the IGWO algorithm outperforms GA, VNS, TS, and standard GWO in optimization and computational stability.</p>