Mining Machinery


Manufacturers & Suppliers
Home » Products » » Mining Machinery » Manufacturing & Processing Machinery » Models For Mining Equipment Selection
  • Product Details
  • Company Profile

Models for Mining Equipment Selection
In many industries, materials handling represents a significant component of the operational cost, making equipment selection an important challenge to management. To meet this challenge, extensive research has taken place in the mining and construction industries which are heavily dependant on equipment. Yet this research effort has not resulted in an acceptable solution strategy for these industries. The complexity of the problem is due to the many factors that contribute to the operating expense of equipment. Consequently, available methods can only consider a small subset of the possible combinations of trucks and loaders.

 
This paper addresses equipment selection for surface mines. Given a mine plan, the ultimate objective is to select the trucks and loaders such that the overall cost of materials handling is minimised. Such a fleet must be robust enough to cope with the dynamic nature of mining operations where the production schedule can sometimes be dependent on refinery requirements and demand. Due to the scale of operations in mining, even a small improvement in operation efficiency translates to substantial savings over the life of the mine.
There is a considerable amount of literature concerning shovel-truck productivity for construction equipment selection and shovel-truck equipment selection for surface mines. Although a variety of modelling methods have been applied, such as Queuing Theory, Bunching Theory, Linear Programming and Genetic Algorithms, the solutions obtained are consistently inadequate. In the mining industry current methods use spreadsheets and are heavily dependent on the expertise of a specialist consultant.
Classical Methods include concepts such as match factor, bunching theory and productivity curves. These methods often rely on brute force to achieve a feasible solution, where a handful of truck types may be enumerated by hand for the minimum cost fleet size. Operations Research techniques such as Integer Programming (IP) and Nonlinear Programming have been applied in a bid to achieve an optimal solution. Current IP solutions tend to oversimplify the model or rely on excessive assumptions. More complex constraints can be included in these formulations, which help to describe a more realistic idea of the performance of a particular fleet. Artificial Intelligence techniques such as expert systems, knowledge based methods and genetic algorithms have been applied to equipment selection with some success, although optimality has not been demonstrated in the literature.
Common weaknesses amongst all of these models are fleet homogeneity, loader (or truck) type preselection and restricted number of passes (from loader to truck). Fleet homogeneity assumes that the truck fleet should only consist of one type of truck. Yet there is no reason to believe that a mixed-type fleet underperforms a homogeneoustype fleet. Loader (or truck) type pre-selection requires a highly skilled and experienced engineer to select a loader type based on geographical and geological information. This can be a time consuming task and a demonstration of optimality is unlikely. Although there is a general preference for restricting the maximum passes from loader to truck, there is also no evidence in literature to support this constraint. The equipment type selection should occur alongside fleet size selection if a bid at optimality is desired. Models that consider the condition of pre-existing equipment do not exist in the literature. Some research has modeled the equipment replacement problem but focuses on replacement time rather than optimising the type and number of trucks/loaders replacements.
This paper provides a critical analysis of the various models for surface mining operations, identifying important constraints and suitable objectives for an equipment selection model. A new Mixed Integer Linear Programming model is presented that makes use of a linear approximation of the cost function.



View More »
Send your message to this supplier
* From: Enter your Email
To:
* Message:
* Enter the code
shown on image:
The picture looks not clear? Click to get the verification code
Contact Now
There is no literature available which describes the nature of the radioactivity in the red mud.The siting of the radioactivity, and whether or not it...

Shanghai Xuanshi Machinery Co., Ltd.

China [Beijing]
Contact Now
Aynak tender was not a perfect process, occurring as it did in a difficult environment with a deficient in-country capacity and myriad investment chal...

Shanghai Xuanshi Machinery Co., Ltd.

China [Beijing]
Contact Now
Packaging Detail: Main equipment adopts nude package, easy to lose, damped, damage, broken ones will be paked in wood crate or composite board crate. ...

Shanghai Xuanshi Machinery Co., Ltd.

China [Beijing]
Contact Now
Our Pulverizers are ideally suitable for primary and secondary crushing, with low power consumption and easy maintenance. Every feature of these machi...

Shanghai Xuanshi Machinery Co., Ltd.

China [Beijing]
Contact Now
Our prominent range of Concrete Recycling Equipment, aggregate classifier and water recycling agitators prevents pollution and at the same time recove...

Shanghai Xuanshi Machinery Co., Ltd.

China [Beijing]
Contact Now
Recycle waste concrete and building rubble on-site into reusable material to save time, money & manpower! We can contribute to the profitability of h...

Shanghai Xuanshi Machinery Co., Ltd.

China [Beijing]
Related Search
  • Slotlight Products
Bookmark this page Email this page Make TradeTT.com your homepage
All Offers/Products/Company Profiles/Images and other user-posted contents are posted by the user and Tradett shall not be held liable for any such content. However, Tradett respects the intellectual property, copyright, trademark, trade secret or any other personal or proprietary third party rights and expects the same from others. To see our intellectual property policy and for intellectual property rights click here.