Reliability and maintainability analysis to improve the operation of the limoncello production line

Tsarouhas, Panagiotis; Arvanitoyannis, Ioannis S.

doi:10.1111/j.1365-2621.2012.03019.x

Cited by 7 publications

(6 citation statements)

References 19 publications

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“…Failure analysis, is considered as one of the best ways to evaluate company performance. The analysis of limoncello production line reliability have suggested counting a number of failures, time-between-failures, and time-to-repair of specific production line segments (Tsarouhas & Arvanitoyannis, 2012). The loss of income that the company has not received because of the possibly stopped production process are reflected by such indicators.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The price of production unit, time spent to make production unit and time the production line process was interrupted, also including costs of fixing the problem, are used to evaluate the loss of income. The effectiveness of production line operation time and a time lag of 40 minutes long, which is important for a company to maintain 90% of production line's profitability, was found (Tsarouhas & Arvanitoyannis, 2012). To fix production lines' failures within less than 1 hour is a condition necessary to keep production line's profitability.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Production line operates 89,35% of the time, the rest 10,65% is being repaired. Optimal failure repair time must be within 40 minutes to achieve 90% maintainability (Tsarouhas & Arvanitoyannis, 2012) Operational excellence profitability (OEP) indicators. The OEP indicators that were related to performance time losses (energy consumption, direct labor used) showed cost benefits (in total $1564,27), and those that were related to quality (raw materials loss, packaging materials loss, maintenance labor extra time, maintenance spare parts) were not beneficial (…”

Section: Acknowledgmentmentioning

confidence: 99%

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Financial modeling trends for production companies in the context of Industry 4.0

Kartanaitė

Kovalov

Kubatko

et al. 2021

Investment Management and Financial Innovations

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Over the years, technological progress has accelerated highly, and the speed, flexibility, human error reduction, and the ability to manage the process in real time have become more critical and required production companies to adapt production and business models according to the needs. The demand for real-time decision support systems adapted to these raising business needs is continuously growing. Nevertheless, businesses usually face challenges in identifying new indicators, data sources, and appropriate financial modeling methods to analyze them. This paper aims to define and summarize the main financial/economic forecasting methods for production companies in the context of Industry 4.0. Main findings show forecasting accuracy of up to 96% when combining economic and demand information, optimal forecasting period from 10 months to five years, more frequent use of soft indicators in forecasting, the relationship between company’s size and production planning. Four groups of indicators used in financial modeling, such as (I) production-related, (II) customers’ and demand-oriented, (III) industry-specific, and (IV) media information indicators, were separated. The analysis forms a suggestion for decision-makers to pay more attention to the forecasting object identification, indicators’ selection peculiarities, data collection possibilities, and the choice of appropriate methods of financial modeling. AcknowledgmentThis work was partly supported by Project No. 0121U100470 “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy”.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Acknowledgmentmentioning

confidence: 99%

See 1 more Smart Citation

Financial modeling trends for production companies in the context of Industry 4.0

Kartanaitė

Kovalov

Kubatko

et al. 2021

Investment Management and Financial Innovations

View full text Add to dashboard Cite

show abstract

“…There are several studies in the semiconductive industry (Huang et al, 2003), metal industry (Anvari et al, 2010), rails (Åhrén and Parida, 2009) and airbag safety devices to the automotive industry (Dal et al, 2000). However, the literature in food industry is very limited, and there are few papers, such as Tsarouhas and Arvanitoyannis (2012), that investigated the relationship between the management of a factory and the limoncello production line. The production line did not reach the 85 percent goal, due to speed losses, errors and defective products which were attributed to the maintenance practices of the company.…”

Section: Overall Equipment Effectiveness (Oee)mentioning

confidence: 99%

Improving operation of the croissant production line through overall equipment effectiveness (OEE)

Tsarouhas

2019

IJPPM

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Purpose Overall equipment effectiveness (OEE) is a metric for estimating equipment effectiveness of the industrial systems. The purpose of this paper is to identify maintenance improvement potentials using an OEE assessment within the croissant production line. Design/methodology/approach The present work is carried out by analyzing the failure and repair data of the line. The failure data cover a period of 15 months. During this period the croissant production line usually operates over the entire day (24 h per day) in three 8-h shifts per day, and pauses at the weekends. Descriptive statistics of the failure and repair data for the line based on scheduled and unscheduled interruptions were carried. Moreover, the actual availability (A), performance efficiency (PE) and quality rate (Q) measures, together with the complete OEE for each working day for the croissant production line, were shown. Findings The main objectives are to understand the operation management of the croissant production line, and to measure the OEE characteristics in precise quantitative terms. OEE analysis can help the company to identify the primary problems concerning the A, PE and Q and acts immediately. Originality/value This paper presents a successful evaluation of OEE which will provide a useful guide to aspects of the production process, which identifies the critical points of the line that require further improvement through effective maintenance strategy (i.e. total productive maintenance). Moreover, the analysis provides a useful perspective and helps managers and engineers make better decisions on how to improve manufacturing productivity and quality.

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“…They pointed out that the failure times follow the logistic distribution whereas the repair times comply with the Weibull distribution, and the repair rate of failure increases, thereby implying that the maintenance staff expertise increases with time. In a recent study, Tsarouhas and Arvanitoyannis (2012) carried out reliability and maintainability analysis on a limoncello production line by applying statistical techniques on field failure data.…”

Section: Literature Reviewmentioning

confidence: 99%

Yogurt production line: reliability analysis

Tsarouhas

Arvanitoyannis

2014

Production & Manufacturing Research

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A reliability analysis of an automated yogurt production line was carried out for all machines and the entire line level. Trend and serial correlation tests validated the assumption of independence and identical distribution of the failure data was conducted. The determination of the theoretical distribution parameters that had the best fit to the failure data was made. Furthermore, the reliability and failure rate models for the entire production line were developed. The models could prove to be a useful tool, both to assess the current conditions and to predict the reliability for upgrading the operations management policies of the yogurt line. It was found that: (a) the Weibull distribution provided the best fit for the yogurt production line to describe the time between failures, (b) the failure rate of the production line increased implying that the currently applied maintenance strategy is not adequate and must be upgraded in the near future, and (c) to avoid losses related to quality and productivity, the reliability must be improved initially on the pasteurizing boiler, and secondly on the filling machine.

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Reliability and maintainability analysis to improve the operation of the limoncello production line

Cited by 7 publications

References 19 publications

Financial modeling trends for production companies in the context of Industry 4.0

Financial modeling trends for production companies in the context of Industry 4.0

Improving operation of the croissant production line through overall equipment effectiveness (OEE)

Yogurt production line: reliability analysis

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