The production cycle time in serial production: Reduction of the duration in metal processing industry case

Possible hazards of work environment in metal processing industry in Latvia The aim of this study was to investigate risk factors in the work environment of Latvian metal processing industry using the database of the Laboratory of Hygiene and Occupational Diseases of the Institute of Occupational Safety and Environmental Health, Rīga Stradiņš University. During the period between 1996 and 2005, 703 measurements were made in metalworking enterprises. In Latvia, approximately 2.4% of the workforce is involved in the metal processing industry. Physical (noise, lighting, vibration) and chemical (abrasive dust, welding aerosol and contained metals) risk factors were analysed. In the assessed metalworking workplaces, the work environment was estimated to be of poor quality, because occupational exposure limits or recommended values were exceeded in 42% (n = 294) of cases. Noise, manganese and welding aerosols most often exceeded the occupational exposure limits or recommended values, the significance was P < 0.001, P < 0.01 and P < 0.05, respectively.

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Low Emissions Burner Technology for Metal Processing Industry using Byproducts and Biomass Derived Liquid Fuels

10.2172/1133127 ◽

2013 ◽

Author(s):

Ajay Agrawal ◽

Robert Taylor

Keyword(s):

Liquid Fuels ◽

Processing Industry ◽

Metal Processing ◽

Metal Processing Industry

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Greening of production in metal processing industry through process modifications and improved management practices

Resources Conservation and Recycling ◽

10.1016/j.resconrec.2013.06.004 ◽

2013 ◽

Vol 77 ◽

pp. 89-96 ◽

Cited By ~ 16

Author(s):

Emrah Alkaya ◽

Göksel N. Demirer

Keyword(s):

Management Practices ◽

Processing Industry ◽

Metal Processing ◽

Metal Processing Industry

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Metal Swarf and Cutting Fluid Waste Management in Metal Processing Industry

Journal of Metallic Material Research ◽

10.30564/jmmr.v1i1.431 ◽

2019 ◽

Vol 1 (1) ◽

Cited By ~ 1

Author(s):

Nezih Kamil SALİHOĞLU ◽

Zeinab AMIN ◽

Çagla Celikli

Keyword(s):

Hazardous Waste ◽

Cost Savings ◽

Waste Reduction ◽

Cutting Fluid ◽

Process Efficiency ◽

Processing Industry ◽

Metal Waste ◽

Manufacturing Location ◽

Metal Processing ◽

Metal Processing Industry

Metal swarf is unavoidable material in metal processing industry, also metal swarf treatment lead to cost savings by metal waste reduction and removing the cutting fluid waste, that cause to increasing process stability and metal value. It is interested that in how to recycle metal swarf especially when swarf surrounded by cutting fluid, is considered because these waste are classified as hazardous waste. The aim of the study is to increase the process efficiency and environmental performance by metal waste reduction at source which are the first step of the waste hierarchy. The results of the experiments showed that 3391 tons of metal swarf coated with cutting fluids which contained 2.29% cutting fluid be produced annually. It has been found that if the total amount of cutting fluid on the swarf surface be reduced to less than 1% leads to a significant mass reduction in the amount of hazardous waste. In this research, it was considered, 107,922 USD profit at the end of first year and 205,278 USD at the end of second year would be obtained by reducing the cutting fluid content from 2.29% to 0.8% with using cutting fluid that surrounded metal swarf separation equipment in manufacturing location.

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Cogeneration and the Citrus Industry

ASME 1987 Citrus Engineering Conference ◽

10.1115/cec1987-3302 ◽

1987 ◽

Author(s):

Edwin F. Coxe

Keyword(s):

Energy Source ◽

Thermal Process ◽

Power Production ◽

The Other ◽

Citrus Industry ◽

Processing Industry ◽

Metal Processing ◽

Metal Processing Industry ◽

The One ◽

Topping Cycle

The purpose of this presentation is to acquaint you with cogeneration, provide techniques for quickly assessing its possible application at your facility, and provide direction for implementation, if appropriate. Cogeneration is the sequential production of steam and electricity from the same energy source. It is sequential in that the energy first produces electricity and then useful thermal energy. This application is called a topping cycle because the power production precedes the thermal application. It is the one that should be of most interest in the citrus industry, and the one that will be addressed herein. The other configuration, the bottoming cycle, is where the energy source for power generation is from heat recovered from a high temperature thermal process application such as often exists in the metal processing industry. Paper published with permission.

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DETERMINATION OF THE ELEMENTS OF PRODUCTION CYCLE TIME IN SERIAL PRODUCTION: THE SERBIAN CASE

Transactions of the Canadian Society for Mechanical Engineering ◽

10.1139/tcsme-2014-0021 ◽

2014 ◽

Vol 38 (3) ◽

pp. 289-304

Author(s):

Dragan Ćoćkalo ◽

Sanja Stanisavljev ◽

Dejan Đorđević ◽

Milivoj Klarin ◽

Aleksandar Đ. Brkić

Keyword(s):

Cycle Time ◽

Mean Value ◽

Working Time ◽

Experimental Investigations ◽

Time Range ◽

Production Cycle ◽

Distribution Law ◽

Serial Production ◽

Working Cycle

A model for the stochastic determination of the elements of production cycle time is proposed and experimentally verified in this survey. The originality of the model as reflected in the idea of using a work sampling model to monitor the production cycle is one of the most significant indicators of production effectiveness and efficiency, instead of applying classical methods. It has been experimentally proved that for a corresponding representative set the elements of working time range according to normal distribution law and that, dynamically viewed, it is possible to use mean value calculations to establish control limits on three standard deviations for the individual elements of working time and thus to master the process. Based on our experimental investigations, it has been proved that in the practice of small and medium-sized enterprises with serial production it is possible to design and apply a very simple but accurate enough stochastic model to determine the elements of working cycle time and in this way optimize the duration of production cycle time.

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