project management in mining-revised

7/27/2019 Project Management in Mining-revised

1/174

PROJECT MANAGEMENTIN MINING

MER NVER


2/174

CONTENTS

1-BASIC ECONOMICAL CONCEPTS IN PROJECTS.(6)

1.1-Definition of Project and Investment..............(6)1.2-How Sources are Generated for Investments...(13)1.3-Social and Economical Results of Investments......(17)1.4-Project Goals and Objectives.......(20)1.4.1-Management by Objectives.......(21)

2- STATISTICAL APPLICATIONS IN PROJECTS.....(24)

2.1-Probability...(24)2.1.1- A Priory Probabilities..(25)2.1.2-Empirical Probability..(25)2.1.3-Addition Law of Probability ..(26)2.1.4-The Multiplication Law of Probability...(27)2.2-Averaging...(28)2.2.1-Arithmetic Mean.....(28)2.2.2-Harmonic Mean...(28)

2.2.3-Geometric Mean..(29)2.3-Frequency Distributions.........(29)2.3.1-Types of Distributions....(32)2.3.1.1-Discrete Distributions...(32)2.3.1.2-Continuous Distributions..(32)2.4- Variance.(33)2.5- Risk and Confidence..(39)2.6-Regression and Correlation........(42)2.6.1- Simple Linear Regression ..(43)

2.6.2-Multiple Linear Regression.(47)2.6.3-Non-Linear Regression(50)

3-PRESENT AND FUTURE MARKET TRENDS.(51)

3.1-Introduction(51)3.2-Analysis of Past and Present Demand...(51)3.2.1- Quantitative Information....(52)3.2.1.1-Information Relating to Physical Quantities.52)

3.2.1.2-Statistics Related To Prices..(53)3.2.2- Qualitative Information..(53)

22


3/174

3.3- Different Methods of Estimation Future Demand...(53)3.3.1-Projection of the Trend...(54)3.3.2-Utilization of Technical Coefficients.(54)3.3.3-International Comparison....(54)

3.3.4-Possibilities of Export or Import Substitution....(55)3.3.5-Econometric Methods..(55)3.3.5.1-Relationship Between Demand and Price....(55)

4-FORECASTING..(57)

4.1- Collective Opinion.(57)4.2-Time Series Analysis..(57)4.3-Semi Average Method....(58)4.4-Moving Average Method59)4.5-Method of Least Squares...(59)4.51-Straight-Line Equation.(60)4.5.2-Parabola Equation(61)4.5.3-Exponential Equation..(62)4.6-Standart Error of Estimates...(63)4.7- Reliability Range of Forecast......(66)4.8-Regression and Correlation in Forecasting.(66)

5-CONTROL OF PROJECTS-CPM AND PERT METHODS(66)

5.1-Objectives of Project Control.(66)5.2-The Gantt Chart..(67)5.3-Drawing the Activity-on-Arrow Network..(70)5.3.1-Activities of a Project..(70)5.3.2-Events of a Project..(70)5.3.3-Precedence Relations...(71)5.3.4-Conventions Adopted in Drawing (AoA) Networks..(71)5.3.5-The Physical Construction of Diagrams.(71)

5.3.6-Fundemental Properties of Events and Activities..(73)5.3.7-Two Errors in Logic....(73)5.3.8-Dummy Activities..(74)5.3.9-An Example of a (AoA) Diagram..(77)5.3.10-Who Should Construct Diagrams..(79)5.3.11-Who Should Make Time Estimates...(79)5.4-The Analysis of Networks (CPM).(79)5.4.1-Activity and Event Times....(79)5.4.2-Critical Path.....(81)

5.5-Estimating the Duration of Project Activities(83)5.5.1-Deterministic Approach..(85)

33


4/174

5.5.1.1-Modular Technique...(85)5.5.1.2-Benchmark Job Technique....(86)5.5.1.3-Parametric Technique(86)5.5.2-Stochastic Approach.(86)

5.6-PERT.......(91)5.6.1- Dealing With Uncertainty(92)5.6.1.1-The Monte Carlo Simulation.(92)5.6.1.2-The PERT and Extensions.(95)5.7-Techniques for Managing the Project Budget.(104)5.7.1- Slack (float) Management...(104)5.7.2-Crashing(108)5.8-Resource Management....(112)5.8.1-Effect of Resources on Project Planning.(112)5.8.2- Classification of Resources Used in Projects..(112)5.8.3-Resource Leveling Subjects to Project Due-Date Constraints.(114)5.8.4-Resource Allocation Subjects to Resource Availability Constraints...(123)5.9-Computer Support for Project Management(124)5.9.1- Introduction..(124)5.9.2-The Microsoft Project...(125)

6-PROJECT COST .(126)

6.1-Capital Investment Cost.(126)

6.1.1-Transport and Insurance Costs....(128)6.1.2-Import Taxes and Custom Duties....(128)6.1.3-General Expenditures..(128)6.1.4-Unforeseen Costs(128)6.1.5-Interest During Investment.(129)6.1.6-Working Capital.(130)6.2-Principal Sources of Error in Estimating Costs.(130)

7-THE CONCEPT AND ANALYSIS OF PROFITABILITY(131)

7.1-Nature of Profits..(131)7.2-Projects and Profits.(131)7.3-Measurement of Expected Profits...(132)7.4-Present Value of Expected Earnings Criterion(134)7.4.1-The Concept of Discounting Back to the Present.(134)7.4.2-Choice of the Rate of Discount.(138)7.4.3-The Discounting Period....(139)

7.5-Practical Problems of Application of the Present Value Criterion..(140)7.6-The Internal Rate of Return Concept (IRR)...(141)

44


5/174

7.7-How to Determine the Cash Flow.(146)7.8-Variation in Grading of Projects by Variation in Discount Rate..(147)7.9-Profitability Criteria Derived from the Simple Accounting Approach.(149)

8-CONTRACTS IN PROJECT MANAGEMENT....(149)

8.1-Introduction..(149)8.2-Precontractual Works...(150)8.2.1-The Specification..(150)8.3-The Contracts...(152)8.3.1-Type of Contracts According to the Mode of Payment(152)8.4-The Conditions of a Contract...(153)8.5-Management of Contracts....(159)

9-CONFLICT MANAGEMENT..(160)

9.1-Conflict at the Individual Level.(160)9.2-Conflict at the Organizational Level..(160)9.3-Conflict Between Organizations.(162)9.3.1-What Triggers Claim and Disputes.(163)9.3.2-Disputes Regarding contract Interpretation(164)9.3.3-Subsurface,Changed, and Differing Conditions.(165)9.3.4-Claims Due to Scheduling Problems.(165)

9.4-Arbitration and Mediation.....(166)9.5-Dispute Resolution in International Contracts...(167)9.5.1-Jurisdiction (168)9.5.2-Choice of Law....(168)9.5.3-Choice of Forum....(168)9.5.4-Alternative Dispute Resolution..(169)9.5.5-Performance Bond..(169)9.5.6-Advance Payment Bond.(170)

55


6/174

1-BASIC ECONOMICAL CONCEPTS IN PROJECTS

1.1-Definition Of Project And Investment

We all deal with projects in our daily lives and it is interesting to note that,projects have been carried out as long as humans have existed. In most cases,organization and management simply amount to construction of a list of tasksand executing them in sequence, which normally consume resources. Theseresources are generally men, money, machines, and materials.

Projects may involve expenditures amounting to millions of dollars expendituresand several hundreds of people who need to be managed and coordinated. Theyneed to know what has to be done, who should do it, when it should be done, howit will be done, and what resources will be used. Proper planning is the first stepin communicating these intentions.

No definition of a project will suit every situation. However, general definition,which suits the engineering disciplines, may be stated as follows:

Project- unique process, consisting of a set of coordinated and controlledactivities with start and finish dates, undertaken to achieve an objectiveconforming to specific requirements including constraints of time, cost and

resources.

All projects pass through at least four identifiable phases; the conception, thedevelopment, the realization and the termination.

Figure 1- The four phases of a project

Many of the most difficult engineering challenges of recent decades have beento design, develop, and implement new systems of a type and complexity never

66


7/174

before attempted. Examples include the construction of vast petroleumproduction facilities in the North Sea, opening up of new mines with productioncapacities and ore grades never attempted before, the development of mannedspace program, the installation of fiber optic lines for broadband

telecommunication and the development of cellular mobile phone systems. Thecreation of these systems with performance capabilities not previously available,and within acceptable schedules and budgets, has required the development ofnew methods of planning, organizing, and controlling events. This is the essenceof project management.

Management of a project differs in several ways from management of a typicalenterprise. The objective of a project team is to accomplish its prescribedmission and break up. Since a project is intended to have a finite life, with theintention of building a career with the project, employees are seldom hired.Instead, a team is pulled together among people who normally have assignmentsin other parts of the organization. They may be asked to work full time on the

project until its completion; or may be asked to work only part time, such as twodays a week, on the project and spend the rest of the time at their usualassignments. A project may involve a short- term task that lasts only a matter ofdays, or it may run for years. After project completion, the team normallydisperses and its members return to their original jobs.

The presence of uncertainty coupled with limited experience and hard- to-find

data makes project management a combination of art, science, and most of all,logical thinking. A good project manager must be familiar with a large numberof disciplines and techniques. Knowledge is particularly important because most

projects have technical, economical, financial, marketing and organizationalaspects that inevitably work against to change the plans.

It is essential and perhaps the most difficult part of the project managementfunction is to pay close attention to the entire picture without losing sight tocritical details, no matter how small. The project manager has to differentiate

different aspects of the project each time and a decision is called for. Questionslike: How important is the budget relative to schedule? and Should moreresources be acquired to avoid delays at the expense of a budget overrun, orshould a slight deviation in performances be tolerated as long as the project iskept on schedule and on budget? are common.

Some skills can be taught, whereas others come only with time and experience.We will not dwell on these but simply point out them as an attempt to definefundamental principles and procedures. Nevertheless, one of our basic aims is to

highlight the practical aspects of project management and to show how modernorganizations can function more effectively by adopting them.

77


8/174

The Project Management Institute identifies six basic functions that thediscipline must address.

Manage the projects scope by defining the goals and the work to be donein sufficient detail to facilitate understanding and corrective action, shouldthe need arise.

Manage the human resources involved in the project. Manage communications to see that appropriate parties are informed and

have sufficient information to keep the project on track. Manage time by planning and meeting a schedule. Manage quality so that the projects results are satisfactory. Manage costs so that the project is performed at the minimum practical

cost and within budget, if possible.

Managing a project is a complex and challenging assignment. Since projects areone-of-a-kind endeavors, there is little in the way of experience, normal workingrelationships, or established procedures to guide the team participants. A projectmanager may have to coordinate many diverse efforts and activities to achieve

project goals. Persons from various disciplines and from various parts of theorganization who have never worked together may be assigned to the project fordifferent spans of time. Contractors who are unfamiliar with the organization

may be brought in to carry out major tasks. The project may involve thousand ofinterrelated activities performed by persons employed by any one of the severaldifferent subcontractors.

Thus, it is important that the project leadership have an effective means ofidentifying and communicating the planned activities and theirinterrelationships. A computer-based scheduling and monitoring system isusually essential. Network techniques such as CPM (critical path method) andPERT (program evaluation and review technique) are likely to figure

prominently in such systems. CPM was developed in 1957 by J. E. Kelly ofRemington - Rant and M. R. Walker of Dupont to aid in schedulingmaintenance and shutdowns of major chemical plants. PERT was developed in1958 under the sponsorship of the U.S Navy Special Projects Office, as amanagement tool for scheduling and controlling the Polaris missile program.Collectively, their value has been demonstrated time and again during both the

planning and execution phases of projects.

In general, project management need enthusiasm, stamina, and appetite for hardwork to withstand the difficulties of technical and non-technical problems. The

ability to trade off or substitute conflicting goals and to find the optimal balancebetween conflicting pressures is probably the most important skill of the job.

88


9/174

Project management, where possible, should have seniority and position in theorganization equal with that of the functional managers with whom they mustdeal. Therefore they must have a blend of technical, administrative, andinterpersonal skills as illustrated in Fig.2 to establish effective leadership.

Figure 2-Important skills for the project manager

Generally speaking, an investment, whether industrial or not amounts to theconsumption in the near future of scarce or at least limited resources in the hopeof obtaining in return over a longer period some benefit, whether financial ornot. The income received from sale of a product is a financial benefit, whereasthe availability of a school or a hospital is a social benefit. The period duringwhich the company or the community will enjoy this benefit will have to besufficiently long to justify the initial consumption of scarce resources.

Converting a wheat field into an orchard amounts to foregoing the use of ascarce resource, land, for some years, and therefore of the benefit (profit)

99


10/174

derived from the sale of the wheat which could have been harvested from it, inthe hope that the ultimate output of fruit will procure a benefit (profit) far higherthan that obtained from growing wheat.

To make an industrial investment is therefore to exchange immediateexpenditure against future monetary income. Also a social investment amountsto exchange immediate expenditure against future social benefit. Whether theoutcome is a profit or a benefit it has to be measurable it order to find

justification for the investment In this course we will concentrate on thejustification of industrial investments.

The resources channeled into an investment are particularly scarce. Thus it isnecessary to ensure optimum use is made of them. The projects must be

planned, analyzed and implemented with great care. Here we would like tostress on the importance of project management. To ensure the optimum or inmost of the cases maximum use of physical inputs in an industrial project, themanagement of a project starts from the very initial stage of thinking and

planning (conception), the development (design and specify), the realization-full capacity running of the project and the termination.

We will define project management as depicted in Figure 1, the coverage of allactivities starting from the initial stage of thinking and planning, thedevelopment, the realization and the termination of the project.

Investments are made for different reasons; to meet the demand of the market, torenew the main production machinery because the old one may be runningcostly or inefficiently, to increase the production capacity of the mine orenrichment plant or to betterment of production quality, but in all cases with thehope of obtaining a financial profit or a benefit. Here by benefit we mean allthe gains or financially profits generated throughout the life of the investmentand by cost the capital investment made to that industrial project, then thefollowing expression has always to be greater than one.

COST

BENEFIT

1The type of investments generally governments undertake are typically socialinvestments such as investment in schools, roads, irrigation, hospitals and otherinfrastructure projects. However private investments are usually channeledtowards meeting the market demand.

Here one feels to differentiate between consumption and investment. Actually

during the investment of a project we consume our financial resources with thehope of obtaining in return a financial benefit, which is higher than the

1010


11/174

investment. However consumption results in expenditure to meet our needs. Arefrigerator bought for your home is consumption, but a refrigerator bought bythe grocer for the grocery is an investment.

Investment is an economic activity and is dependent on general economicconditions. Investments are volatile component of Gross National Production(GNP), which we will explain in the pages to follow, falling sharply duringrecession and rising sharply during economic booms. It may be that a 3% fallin GNP may result 18% fall in investments or a 4% rise in GNP results 13% risein investments, as was the case in USA in early 80s.

A specific investment opportunity may be quite attractive to one prospectiveinvestor yet totally unacceptable to another. This difference in desirability canresult from each of the prospective investor having different commercialcapabilities, capital availability or cost, alternative opportunities or acombination of them. Consequently, investment desirability does not seem alikely candidate for a positive selection technique or amenable to measurement,

by a single numerical criterion. Although the positive approach of ratingcomparative desirability does not appear practical, the reverse approach ofscreening out and rejecting undesirable proposals does appear workable.However even rejection can be a relative matter, or it can involve relationships

between two or more criteria. For this reason, to choose the best project,involves evaluation yardsticks rather than decision techniques.

There are different types of investments. For our purpose, which fits themanufacturing or the mining (production) industries best, we will differentiatethree types of investments.

New Investments: This investment covers the development of a newmining project and all related expenditures to realize the project.Construction and development of a new coalmine to feed a power plant to

produce electricity or to feed an iron and steel mill to produce steel are

examples of a new investment.

Expansion Investments: This investment covers the expansion of anexisting plant as well as investments made to increase the plant capacity

by adaptation of new technologies. Investments undertaken to increase theproduction capacity of a copper mine from 2.000.000 tons/year to4.500.000 /year is an expansion investment. Similarly investmentinvolved in increasing the capacity of a coal washing plant is anexpansion investment.

1111


12/174

Investments for Renewal and Modernization: This type of investmentis related to replacement of the existing plant, because the old machineryand equipment involved in the manufacturing or production process canno more function properly or produce goods with the desired precision,

quality or cost. In an open cast mine changing the carrying capacity of thedump trucks from 100 tons to 230 tons because of production costadvantages of the former is an example of the renewal investment.Because of high manufacturing or production costs it may be necessary toinvest in new machinery and equipment to decrease the costs. The qualityof the product may not meet the requirements of the market or thecustomer, such as the grade of the concentrate from the enrichment plant,thus it may be unavoidable to invest in new machinery and equipment inorder to betterment of quality of the concentrate.

In mining unique to other industries to achieve constant output new mainroads and/or shafts has to be developed which involves considerablevolume of investments to serve for a period of time. These works areconsidered as investments made to continue production without a fall inthe output. However in other manufacturing and production industrieswhen initial investment is done to continue production no otherinvestment is necessary other than renewal and modernization. Thus inmining a deposit continuous investment is necessary throughout the life ofthe mine.

New and expansion investments are more market oriented or seek possibleopportunities to increase the profits related to capital. However renewal andmodernization projects may be unavoidable since they aim for continuation ofthe enterprise otherwise it may be not possible to market the product withexisting quality or manufacturing cost. In renewal and modernizationinvestments the definition of the problem is of outmost importance. Why there isa need for renewal? Is it because the old equipment is no more capable of

producing the designed production capacity, i.e., the mechanical availability of

the plant is low or is it the case that the cost of maintaining the old plant isprohibitively high. Is it the case that the quality of manufacturing can no moremaintained by the operation of the old plant. A new technology for the

production of the goods may be available or a new design in machinery for theproduction or manufacturing process. What is the economy or profitability aswell as the technical feasibility of these investments, is the problem to beanswered. Before the technical analysis of the question the definition of the

problem has to be put forward with precision.

To achieve our industrial aims we invest. We invest in men, machines, materialsand money. Before decision is made for investment we analyze the market as

1212


13/174

well as the technology involved in the production of the mining product. Thusinvestment in a mining project involves the management of;

Men

Money Machines Materials Market Mining

After project implementation the subject of industrial management is stillidentical to the abovementioned main subjects of management. Thus it can bestated that project management, which involves investments has by all means nodifference than management in the general sense.

1.2-How Sources Are Generated For Investments

Before explaining how capital sources are generated for investments it may beuseful to understand the operational mechanism of the national economy.

The operation of any economy is based on the balance of sources andexpenditures. The relative greatness of the sources and expenditures define therelative standing of the economies.

What are the sources of economy? The classical economists define these sourcesas:

Natural Sources Capital Labor

However in our days a fourth factor is considered as a source to the nationaleconomy. This factor is Management.

The natural sources are;a) Agricultural fields

b) Water potentialc) Mineral resourcesd) Forests

The existence of the above mentioned natural sources have great influence onthe production within a country.

1313


14/174

Capital is a pre- produced value, which is essential in production of goods andservices. Capital goods, then, represent produced goods that can be used asfactor inputs for further production.

From the standpoint of national economy increase and formation of capital playsa major role in the development of an economy. This can only be achieved bydirecting the expenditures to investments in industry.

Labor is also considered as the sources of an economy. When we speak of laborwe cover all working people and people who are willing to work. Theemployment of all people in the production of goods and services is the ultimategoal in all- economical thoughts. The relative skills and working sectors(agriculture, manufacturing, mining, services etc.) of the labor is in closerelation with the development of production.

Management is considered to play the main role in achieving development intechnology and production. Management sources are scarce in all economies.The functions of modern management involve the invention of possible meansof economical production, new markets, new products, development andoptimum utilization of resources, etc. Thus besides minimizing the loss ofsources by making best use of them, management considers deriving benefitsfrom the unused sources that has not been considered beforehand.

We had declared that the operation of an economy is based on the balance ofsources and expenditures. Very shortly we have discussed the sources. Now weshall discuss the expenditures. It is obvious that the total sources gained within a

period of time in a country will be spent and some will be saved and by capitalinvestments will be transformed as capital. In developing an economy the basicaim is to accelerate the formation of capital. This can be achieved byinvestments. Intelligently planned and properly implemented investments inindustry would give huge benefits in the formation of new capital, employmentof people and meet the demands of the society.

It will be of great use to explain further the need for investments for economicaldevelopment. From which sources we find the possibility of investing? To bemore analytical let us deepen our analysis. The national income within a societyconsists of the sum of consumption expenditures and savings or investments. Anincome independent from who owns it and for what services has been received itcan have only two alternatives when spending that income:

To meet the daily requirements for living: consumption.

Invest or save.

1414


15/174

Thus, the national income or the National Product, can be expressed by thefollowing relation:

NP = C + I

Where;NP: National ProductC : ConsumptionI : Investment or Savings

If we try to show the development of national income against consumption,theoretically we will have the following relation.

C+I

Investment orsavings

NPNational income orNational product

Figure 3-Relation of national income to consumption and investments

45tanNP

IC

Thus a dNP increase will result an increase which is equal to dC+dI .Why that isso is obvious, because it is rational to think that a society can consume andinvest what it produces to get equal balance of payments.

Now let us analyze the consumption trend within a society. By increase ofnational income the consumption will increase at the same rate to a certain level

of income, after further increases, it is most probable that when the basic needs

1515


16/174

are satisfied and people would have enough potential to save or invest to getbenefits from their incomes.

Figure 4- Relation of national income to consumption

Combining Fig 3 and Fig 4 together we have the following situation

Figure 5- Development of consumption against national income

In figure 5 the hatched area is of outmost importance, because it shows thecapability of a society to invest or save. Since the 450 line is the sum ofconsumption and investment then we can conclude the relation in Figure 6.

1616


17/174

Figure 6- Development of investments or savings against national income

In figures 5 and 6, point B is the income level within a society where thetendency to save or invest begins. At this point the income level satisfies the

basic needs or requirements of units within the society.

Up to this point we tried to explain the development potential of an investmentwithin a society.

1.3- Social and Economical Results Of Investments

Investments are the dynamic factors in development of an economy ordevelopment of national income. National income; being in direct relation withthe wealth possessed by a nation, the results of investments are, both economicaland social. In other words by economical development social development isinevitable. More analytically the economical results of investments can beanalyzed by the development of capital. The social results of investments can

be analyzed within the context of technological development and shiftingfrom agriculture to industry.

The economical results of investments within the context of development ofcapital have two effects; namely the multiplier and the acceleratoreffects. Every industrial investment emerging from the location of investmentwill create a flow of income and expenditure. People directly involved in theinvestment (employee, contractors, subcontractors, etc.) will develop theirincomes and expenditure potentials. From the consumption expenditures ofthose people directly involved in the investment a flow or spread of incomewould be reflected to second and third group of people who are not directly

involved in the investment. This is called the multiplier effect of investments. Toexplain the multiplier effect of investment in developing the national income, let

1717


18/174

us refer to figure 6. The ratio of dI to dNP determines the marginal savings trendwithin a society.

If the ratio of dI/dNP=0.2, that is to say, if the society is determined to save 1/5

of every $ on the average, then an investment of 1 billion $ will increase theincome of the society by 1 billion $. The income received by the society if savedby 1/5 on the average, will spend 800 million $ to consumption. Since, thisconsumption will create new incomes and employment to other people, these

people will tend to save on the average 1/5 of their income and spend 640million $ to consumption. This will continue each time the income receiveddecreased by 1/5. Where the income increase has stopped it will be seen that aninvestment of 1 billion $ creates an increase in national income by 5 billion $.

Since by figure 3 it is obvious that: dI/dNP + dC/dNP = 1, for the above exampledC/dNP = 0.8 or 4/5, where by definition dC/dNP is the marginal consumption

Figure 7- Multiplier mechanism

In figure 7 as a result of new investment I-I is shifted to I-I. This will cause anincrease in national income from D-D: Thus for every increase in investment by10 units national income is increased by 50 units.

The vector D D has two components; vertical and horizontal. Horizontalcomponent of this vector is 5 times the vertical component. It is obvious that forevery unit of investment there are 4 units of consumption.Investments initiate other investments. Let us take a simple case of underground

coal mining. To produce coal we have to provide mining machines, supports,belt conveyors, electricity, explosive materials etc. In other words we have to

1818


19/174

consume certain industrial goods. Since there is consumption, we have raised aneed, which has to be met by some means. Thus we have created a market, orwe are a market for our consumption. In other words our requirements, initiates,or accelerates other investments. This is called the accelerator effect of

investments.

In the above discussion it is interesting to observe that the national incomedevelopments are independent of who realizes the investments.

Technological development is also realized as a result of investment. Deepeningof capital is realized, which means allocation of more capital per labor. Thenature and quality of the products of industry are improved. Products, which are

produced by handicraft, are no more consumed extensively, they are consideredas inferior. Thus products, which are more strong and high in quality and morein quantity, are produced. Also by technological development shifted to morecapital oriented organizations.

Nearly all economical thoughts agree with the number of people working inagriculture has an inverse ratio with the economical development. Thus byindustrial investments populations working in the agricultural sector are shiftedto more productive sectors; the industry. However it must not be forgotten thatindustrial development is quite impossible without improving the traditionalcharacter of agriculture.

Up to this point we have dealt with the economical and social implications ofinvestments within a society shortly. It is of great importance to realize the

planned results when we make decisions on investments. With wronginvestment decisions we will be the victims of spending our sparse economicalvalues, for less beneficial results. Here it must be stressed that ourresponsibilities to the society as people of industrial origin are huge. By ourdecisions for industry we alter the economical and social values. How we canhave more intellect on the industry we work for and for the society we live in. At

this point we can only admit that such an intellect is in situ of the individuals,however, education is only one of the means of improving it. Is there a need forscientific management is a common question raised in industry? We can onlyanswer this question by stating that to construct and operate an industry there arefour resources; capital, labor, materials, and management, where the latter is aresource which coordinates the other three factors. To avoid inefficientutilization of these resources management knowledge and talents are needed andeducation is a means of development.

1919


20/174

1.4- Project Goals and Objectives

Just as important to know the destination before setting out on a journey, so it isimportant to identify and define precisely as possible the objectives the project is

to achieve. The clear objective . to build housing for new settlement for lowincome families, to launch a new television set with better vision, to construct athermal power plant for electricity generation, to mine and enrich a deep layingcopper deposit with a very low grade economically will obviously known at the

beginning. It is the implicit or inherent objectives, which need to be carefullythought before any sensible plan can take place. For instance, if we consider the

project mining and enriching a deep laying copper deposit with a low gradethen, most probably the project objectives and goals could be the following:

Since we are involved in mining a deep laying copper deposit, the cost ofmining may be high. Thus all possible cost reduction means has to beconsidered in the project design such as; utilization of high productivityin mining machinery to be chosen, design for high efficiencies inutilization of the labor force, etc.

To complete the project as quickly as possible, so that the investmentcosts are not affected from delayed completion.

The enrichment process has to be worked out in precision and care, sincethe ore is of low grade, which means costly to beneficiate.

In the construction of the mine and beneficiation plant subcontracting

prices should be negotiated. The schedule should be followed with precision. Any over employment in the workforce during construction and

operation of the project should be avoided. If there is any cost overrun in any sub activities, remedial measures

should be immediately taken.

Independent from the type of project or project management, every project hasan objective. The objectives are generally expressed in relation of anticipated

project costs, completion of the project according to project schedule, andmeeting the quality standards as laid out in the detailed engineering design.

The system of managing the projects by objectives or goals is a process wherebythe superior and subordinate managers of the company jointly identify the

projects common goals, define each individuals major areas of responsibility interms of expected results, and use these measures as guidelines for projectimplementation of the project team and assessing the contribution of each of itsmembers.

2020


21/174

Any project must build a true project team and weld individual efforts into acommon effort. Each member of the project team contributes somethingdifferent, but they must all contribute towards project goals. Their effort must all

pull in the same direction, and their contributions must fit to produce a whole-

without gaps, without friction, without unnecessary duplication of effort.

1.4.1- Management by Objectives

To achieve our aims we have to manage by objectives during the construction aswell as during the operation of the project. This is simply called Managementby Objectives. To manage by objectives we have to plan from the very start ofthe project preparation, decision for investment, construction of the project andthe operation of the mine.

Independent from the type of industry, every enterprise has an objective. Theseobjectives are usually expressed in profit and sales forecasts, production targets,investment and research budgets and so on.

There are eight areas in which objectives and results have to be set:

Market standing, innovation, productivity, physical and financial resources,profitability, managers performance and development, workers performanceand attitude, public responsibility.

Market standing has to be measured against the market potential, and against theperformance of suppliers of competition products or services- whethercompetition is direct or indirect.

We dont care what share of the market we have, as long as our sales go up isa fairly common comment. It sounds plausible enough; but it does not stand upunder analysis. By itself, volume of sales tells little about performance, resultsof the future of business.

There are two kinds of innovation in every business; innovation in product orservice; and innovation in the skills and activities needed to supply them.Innovation may arise out of the needs of the market and customer. Or it maycome out of the work on the advancement of skill and knowledge carried out inschools and the laboratories, by researchers, writers, thinkers and practitioners.

Productivity is the only yardstick that can actually gauge the competence ofmanagement and allow comparison between managements of different units

within the enterprise, and of different enterprises. For productivity includes allthe efforts the enterprise contributes; it excludes everything it does not control.

2121


22/174

Only an analysis of productivity, which would show how the two companiesutilize their respective resources and how much profit they get out of them,would show which company did the better managing job.

To set objectives without planning for the money needed to make operations, islike putting the roast in the oven without turning on the flame.

Profit serves three purposes. It measures the net effectiveness and soundness of abusinesss efforts. It is indeed the ultimate test of business performance. It is therisk premium that covers the cost of staying in business- replacement,obsolescence, market risk and uncertainty. Seen from this point of view there isno such thing as profit; there are only costs of being in business and costsof staying in business. And the task of a business is to provide adequately forthese costs of staying in business by earning adequate profit.

Profit ensures the supply of future capital for the innovation and expansion,either directly, by providing the means of self-financing out of retained earnings,or indirectly, through providing sufficient inducement for new outside capital inthe form in which it is best suited to the enterprises objectives.

Profitability is meaningless and misleading unless we know for how many yearsthe profit can be expected. We should therefore always state the anticipated total

profits over the life of investment discounted for present cash value, rather than

as an annual rate of return. Besides that, we should always consider the rate ofreturn as an average resulting from good and bad years together. The businessmay indeed need a profit of 25 per cent before taxes. But if the 25 per cent are

being earned in a good year they are unlikely to be earned over the lifetime ofthe investment. We may need a 40 per cent return in good years to average 25

per cent over a dozen of years. And we have to know how much we actuallyneed to get the desired average.

It is fairly easy to determine what objectives are needed for manager

performance and development. A business to stay in business and remainprofitable needs goals in respect to the direction of its managers by objectivesand self control, the setting up of their jobs, the spirit of managementorganization, the structure of management and the development of tomorrowsmanagers.

When we come to setting objectives for workers performance and attitude, tothink through the problems and in this area to arrive at meaningfulmeasurements is one of the great challenges to management. The objectives in

this area should include objectives for union relations. Union relations no matterhow important, are however only a small and peripheral part of the management

2222


23/174

work and the worker. In this area the main things we can measure can be matterslike; turnover, absenteeism, safety, calls on the medical department, suggestionsystem participation, grievances, employee attitudes, etc.

Public responsibility is an area where managers may find it difficult to lay downobjectives without causing a commitment in financial terms. However theseobjectives have to be set according to the social and political conditions, whichaffect the enterprise on the basis of the beliefs of each management. It is thismakes the area so important; for in it managers go beyond the confines of theirlittle world and participate responsibility in the society.

It is always stimulating and constructive to look a fresh and critically at thecompanies forward plans, particularly as the range of objectives is often foundto be dangerously restricted. A broad framework of company objectives, say, forthe next four or five years is of great value even though it is difficult to create.One way to make a start is for the Chief Executive Manager to ask hisimmediate subordinates - the senior executive and functional managers toanswer individually such questions as:

What sort of industry we are really in? What is our distinctivecompetence?

Who are our customers? Who really governs the final decision to buy? What return we are getting on our assets or what profits we are making as

compared to our capital? How does it compare with other companiesworking in the same line of production?

What problems in our business are so critical to day that failure to solvethem could jeopardize our future? What plans do we have to solve them?

What are the significant opportunities we should be exploiting much morevigorously? What plans do we have to exploit them?

What kind of business in size, markets, products, physical facilities, andso on do you think we will have in five years time?

By clarifying some of the above questions we can derive out an objective formanagement or we create a strategic plan for running the industry.

2323


24/174

2- STATISTICAL APPLICATIONS IN PROJECTS

In the design and implementation of any engineering project it is necessary tomake use of factual data to reach for solutions. Thus in the design of a mining

project we have a series of figures by which we make our decisions.

The term statistics pertains to a listing of facts, to systematic methods ofarranging and describing the data, and finally to a science of inferringgeneralities from specific observations. There is a general theory of statistics,which is applicable to any field of study in which observations are made.Statistical procedures form an important part of all fields of science andengineering. There are however, statistical procedures, which are morefrequently used. We shall concentrate on those procedures, which are morewidely used in project management.

2.1- ProbabilityThere are certain notions, which are impossible to define adequately. Suchnotions are found to be those based on universal experience of nature.Probability is such a notion. The dictionary tells that probable means likely.As the words imply probability is a vague general comment. Thus there is aneed to make a numerical statement on how much probable or what is the

probability of something to occur.We measure probability by providingourselves with a scale, called the probability scale, marked zero at one end and

unity at the other.

Figure 8- The probability scale

2424


25/174

The top end of the scale, marked with unity or 1, represents absolute certainty.Any proposition about which there is no doubt at all would find its place at this

point on the scale. For example, the probability that your producing oil well willdeplete some day is an absolute certainty, which is equivalent to the statement

that every living creature will die some day. To define the probability of theabove statement we shall write p=1, the letter p standing for probability. Thebottom end of the scale, marked zero or 0, represents absolute impossibility. Forinstance; the probability that you can run your excavators without anymaintenance and repair for 100 years is an absolute impossibility, which isequivalent to the statement that you could swim the Atlantic Ocean. To definethe probability of the above statement we shall write p=0.

To the human mind there is presented an unending stream of problems thatcannot be given a clear- cut answer of the type p=1 or p=0. The thing to noticehere is that, there is no greater certainty than p=1, and nothing less likely than

p=0. How do we arrive at an actual measure of probability of any real life event?There are two ways, a priory probabilities and empirical probabilities.

2.1.1- A priory probabilities

These are probabilities, which we feel certain we can specify in the magnitudefrom consideration of the very nature of the event. The probability that I spin alira it will come down heads is easily and sensibly guessed to be p=1/2.

Intuitively, we fell that the probability of heads, come exactly halfway along thescale in figure 8.

2.1.2- Empirical probability

If we have a dice and roll 600 times, we should expect that each face wouldhave shown uppermost 100 times. What do we mean by expect? We dontreally expect anything of the sort. In fact, we should be rather surprised at thecoincidence if any result gave such perfect agreement with our expectation.

What we really expect is that each face would turn up, roughly 100 times- nottoo roughly of course, or we should suspect bias.

Thus we can express the empirical probability of an event as:

trialsofnumberTotal

eventtheofsoccurrenceofnumberTotalyProbabilit

2525


26/174

For instance if we have an exploration program on a mining license forchromium and drilled 150 holes out of which 25 holes no ore body is met. In ourfurther drillings we may assume the probability of not cutting the ore zone to be:

17.015025P

This empirical method of finding probabilities as the ratio of the number ofoccurrences to the total number of trials is the method that has been used inmany fields of research.

2.1.3- Addition law of probability

Consider the phrase Heads I win; tails you loose. This is the simplest

illustration of the law of addition. To calculate my total chance of winning, Ihave, according to this law, to add up the total probabilities of each of theseveral ways in which I may win. Adding the two probabilities p=1/2+1/2=1.That is absolutely certain that I shall win.

As a simple example let us suppose that we are drilling for petroleum on acertain piece of land with three drill rigs. What are the expected outcomes ofthose drill rigs if all were completed successfully? There are a total of eightequally likely outcome events, which can be displayed in the following table.

Table 1-Ways of outcomes of drilling three wells

Well A Well B Well CDry Dry Dry

Dry Dry ProducerDry Producer DryDry Producer Producer Producer Dry DryProducer Dry Producer Producer Producer DryProducer Producer Producer

The above results can be summarized as follows:

2626


27/174

Table 2- Probabilities of combinations of producers and dry wells

2.1.4-The multiplication law of probability

Now let us take a case where it is required that simultaneous occurrences ofevents take place. In a promising copper mining lease we want to conductexploration in order to decide for the investments involved in the mining project.However the investor may have certain demands when not met has no interest ininvesting in copper. The demands for such an operation are as follows:

The ore deposit must be suitable by opencast mining, The deposit must be suitable for beneficiation, The average copper grade must be above 1%, The ore deposit must contain more than 500.000 tons metallic copper.

The probabilities of the above requisites are evaluated by the engineers and for

each demand the probabilities are as follows:

Probability of open cast..0.75Probability of ore being suitable for beneficiation.0.50Probability of copper grade being above 1%..0.50Probability that the deposit contains more than 0.5 m tons of Cu..0.5

In order to calculate the probability that all these demanded attributes would befound on the copper deposit in question, we use the multiplication law.

P= 0.75 x 0.50 x 0.50 x 0.50= 0.094

Thus we can only be 9.4 % sure that our exploration will show up the demandswe require. It is also noteworthy to state that, mining exploration programs arealways risky and one should be aware of the facts before giving decisions.

27

P (3 dry) 0.125P (2 dry, 1 producer) 0.375

P (1 dry, 2 producer 0.375P (3 producers) 0.125

1.000

27


28/174

2.2- Averaging

The idea of an average is common property. We realize that the purpose of theaverage is to represent a group of values in a simple and concise manner so that,

the mind get a quick understanding of the general size of the individuals in thegroup. It is of the utmost importance to appreciate this fact that the average is toact as a representative.

2.2.1- Arithmetic mean

The arithmetic mean or average of a set of numbers is calculated by totaling theitems in the set and dividing the total by the number of individuals in the set.

N

X

n

i

i

X

1

2.2.2- Harmonic mean

The harmonic mean is the appropriate average to use when we are dealing withrates and prices.

Consider the well known academic example of the airplane which flies round a

square whose side is 100 km, taking the first side at 100 km/hr, the second sideat 200 km/hr, the third side at 300 km/hr, the fourth side at 400 km/hr. What isthe average speed of the plane in its flight around a square?

If we use the arithmetic mean;

hrkmX /2504400300200100

This is a wrong solution, since the different speeds are not maintained for thesame time- only for the same distance. The correct average to employ in such acase is the harmonic mean, which is given by the following formula:

X

nH

1

For the above example of airplane:

The time to travel along the first side = 1 hour

2828


29/174

The time to travel along the second side = 30 minutesThe time to travel along the third side = 20 minutesThe time to travel along the fourth side = 15 minutesHence total time to travel 400 km = 2 hours 5 minutes

= 25/12 hours

Average velocity ishr

km

1225400

= 192 km/hr

Or;

hrkm

X

nH /192

400/1300/1200/1100/1

4

1

2.2.3- Geometric mean

This is the appropriate average to use when we wish to average quantities, whichare drawn from a situation in which they follow a geometric progression or theexponential trend. To calculate the geometric mean, we multiply together all thequantities, which it is desired to average. Then, if there are n such quantities, wefind the nth root of the product. Denoting our n quantities by X1, X2,X3,Xn,we may write the formula for the geometric mean as follows:

n nXXXG ...2.1

Here we must stress that when averaging certain items it is essential to obtain asmuch as possible occurrences of that item so that you can decide the trend of thevariation and use appropriate averaging techniques.

2.3- Frequency distributions

Interpretation of even moderately large amounts of data requires that they be

summarized. This is commonly accomplished by means of frequencydistributions. Rather than attempt to interpret meanings concealed within largenumber of individual values, the data are gathered into groups or classes. Thisfacilitates interpretation as well as numerical computations. Measurements andestimates generally contain error, so it would often be difficult to justify notusing a frequency distribution.

Let us take the porosity measurements of a specific rock for rock mechanicspurposes:

2929


30/174

Table 3- Porosity measurements (20 values)

Table 4- Forming a frequency distribution

Nominal classboundaries

Members Number of members

0.10 0.12 0.10, 0.11 20.12 0.14 0.12, 0.13, 0.13, 0.13,

0.125

0.14 0.16 0.14, 0.15, 0.15, 0.14,0.15, 0.14, 0.15, 0.14

8

0.16 0.18 0.16, 0.17, 0.16 30.18 0.20 0.18, 0.19 2

Table 5- Frequency distribution


Class mark, Xi Frequency, fi fiXi

0.10 0.12 0.11 2 0.220.12 0.14 0.13 5 0.650.14 0.16 0.15 8 1.200.16 0.18 0.17 3 0.510.18 0.20 0.19 2 0.38

The difference between upper and lower boundaries referred to as class interval.In this example all class intervals are equal. This practice is common, but it isnot a necessary condition.

30

0.12 0.14 0.15 0.180.19 0.16 0.17 0.150.16 0.14 0.15 0.130.14 0.15 0.13 0.13

0.14 0.12 0.10 0.11

30


31/174

When data is gathered in this form, the average porosity can be found asfollows:

i

i

f

fMean i

X

=2.96/20 =0.148

For convenience if we plot the above data as a histogram and frequency polygonwe have Figure 9.

Figure 9 Histogram and frequency polygon

The above histogram and frequency polygon can also be drawn as cumulativefrequency polygon.

3131


32/174

Figure 10 Cumulative frequency polygons

From the above figure we can conclude the probability density. We are 100 %sure that the porosity of the rock is less than 20 %, i.e., p=1. We can alsoconclude from the above figure that 20 % of the cases have a porosity of lessthan 12.4 %, i.e., p=0.2. Also by using the dashed line, one can read directlyfrom the graph that 40 % of the cases have a porosity greater than about 14.6 %,i.e., p=0.4.

2.3.1- Types of distributions

2.3.1.1-Discrete distributions

A common die is a cube whose six faces are numbered one to six. When a die isthrown, it will come to rest with one of those faces up. Other possibilities areruled out (the result cannot be something like 2.4 or 5.1). Only the following are

possible: X = 1, 2, 3, 4, 5, 6. Thus the distribution is not continuous. The

probability of the distribution sum to 1 unity, since, one of the several possibleevents must occur.

In a five man committee the number of yes votes recorded must always be 0,1, 2, 3, 4, or 5. Other examples of discrete observations would be; number of

bolts in a box, number of people entering a department store in a day, number ofbirths at a specific time or the number of rays counted in one second.

2.3.1.2- Continuous distributions

3232


33/174

One concept of a continuous distribution is that it is a continuous envelopeconforming to a discrete distribution. Continuous distributions can serve as aconvenient method for determination of the properties of distributions, whichactually consist of discrete points. Figure 11 indicates this concept.

Figure 11- Continuous distribution curve. Vertical lines indicate a discretedistribution enclosed by the continuous curve.

One of the most important frequency distribution is the normal distribution. Itsappearance is that of a symmetrical bell - shaped curve. To any histogram anormal curve can be fitted. Whether or not the curve accurately pictures thefrequency distribution is another matter. The fit may be good or bad. Of coursein this case the area generated by the histogram is equal to the area generated by

the normal curve. There are other distributions where the analysis falls outsidethe scope of this course.

Figure 12 Normal frequency distribution2.4 VarianceWe have discussed various ways of measuring the central tendency or average ofdistributions. Since in all project activities we are dealing with series of data

observed or collected, the average figure gives a good way for judgment. Theaverage or the mean and the most commonly occurring value or the mode

3333


34/174

which is not upset by the extreme values in the distribution can be shown inFigure 13.

Figure 13 The mode and mean values in a distribution

However in our number of data, does the average give us a means ofunderstanding for a clear picture of the differences in the values of data? Or inother words does any average figure itself give a clear picture of distribution. In

Figure 14 Different distributions with equal mean value

Another type of measure, which helps to clarify the shape of the distribution, isone that indicates how the observations are spread out from the average. Such ameasure could be called a measure of dispersion, spread or variability.

At the first glance, the sum of the deviations of the observations from the mean,

3434


35/174

)_

1( X

n

ii

X

may seem to be good measure for this purpose, but on further examination wesee that its value is always zero, where:

Xi = value of the I th observationX= mean value of the observation

For example the arithmetic mean of the numbers 2, 3, 5, 8, is 4.5, so thedeviations from the mean are; - 2.5, - 1.5, + 0.5, + 3.5: The total of thesenumbers is zero.

This objection may be overcome by squaring the deviations before they areadded. This is defined as variance. The variance is the sum of squares of the

deviations of the observations fromX divided by one less than the total number

of observations.

1

)(......)()( 2_

2_

2

2_

12

N

XXXXXXS n

or

1

)( 21

_

2

N

XX

S

n

ii

Where;S2=varianceXi= value of the i th observation_

X = mean value of observation

Standard deviation is the positive square root of the variance. Thus thestandard deviation is given by:

1

)( 21

_

N

XX

S

n

ii

3535


36/174

The standard deviation denoted by, S, is the most important measure ofvariation. In broad sense, it measures the average deviation of each observationfrom the arithmetic mean.

It sometimes happens that we wish to ask ourselves whether one distribution isrelatively more variable than another. Coefficient of variation is the mostcommonly used measure in such a practice.

=_

100

X

S

Where:

= coefficient of variation, (%)S = standard deviation_

X= mean value

Now let us consider the following example where we have a series of tests todetermine the compressive strength of a limestone for mining design purposes.

Table 6- Compressive strength measurement (kg/cm2)

751 833 852 788 828742 758 875 874 753920 847 888 802 789725 901 893 811 815

Table 7 Forming a frequency distribution

Table 8 Frequency distribution


Class mark,Xi

Frequencyfi

fiXi FiXi2

36


Members Number of members(fi)

700 750 725, 742, 2750 800 751, 758, 753, 788, 789, 5800 850 833, 847, 802, 811, 828,

815,6

850 900 852, 875, 888, 893, 874, 5900 950 920, 901, 2

36


37/174

700 750 725 2 1450 1051250750 800 775 5 3875 3003125800 850 825 6 4950 4083750850 900 875 5 4375 3828125

900 950 925 2 1850 1711250Total 20 16500 13677500

N=fi = 20

N

XfX ii

_

= 16500/20 = 825If fi observations have the value Xi then the variance formula is;

1/)( 222

N

NXfXfS iiii

05.342119

20/)16500(13677500 22 S

Thus;

5.5805.3421 S

Coefficient of variation = 100x58.5/825 =7.09 %

Supposing for the same mine design purpose we have tested sandstone and theresults are given as follows:

Table 9 Frequency distribution for sandstone

Xi, (kg/cm2) fi fiXi FiXi2525 4 2100 1102500575 8 4600 2645000625 3 1875 1171875675 2 1350 911250

Total 17 9925 5830625

N = fi = 17

3737


38/174

8.583_

N

XfX ii

1

/)( 22

2

N

NXfXfS iiii

= 2261S= 47.6 (standard deviation)

Coefficient of variation = 100x47.6 /583.6 = 8.15 %

Taking the two- abovementioned examples into account, though the limestone ismore variable in absolute sense, the variability of the sandstone expressed as the

percentage of the mean compressive strength is greater.

We have seen how to calculate the standard deviation. What use is it to us in

interpretation? Actually it is very easy to visualize. If we have a distribution,which is reasonably symmetrical about its average and which is unimodal (i.e.,has one single hump in the center) as shown in figure 15, then we have verylittle error in assuming that 68% of the distribution lies less than one standard

deviation away from the mean or SX 1_

, that 95 % of the distribution lies less

than two standard deviation away from the mean or SX 2_

, and that less than1% of the distribution (99 % of the distribution area) lies more than three

standard deviations away from the mean or SX 3

_

.

Figure 15Unimodal distribution with 100_

X and s=13

3838


39/174

The theory behind these statements which is proved by a Russian mathematicianP.L. Chebyshev is that for real numbers of k, k>1 at least 1- 1/k2 of the values liewithin k standard deviations of the mean (or average). A summarized view ofChebyshevs proof is given in table 10. The meaning of this table is simply that

approximately 68% of the data lies 1 (s) standard deviation away from the mean(average), approximately 95% of the data lies 2 (s) standard deviation awayfrom the mean, and approximately 99 % of the data lies 3 (s) standarddeviation away from the mean. If a population or large a sample symmetricaland unimodal, an estimate is possible for the proportion of data within certainintervals. The estimates in the following table are often called Empirical Rule.

Table 10- The Empirical Rule

Approximately this portionof data Lies within thisInterval

0.682SX 1

_

0.954

SX 2_

0.997

SX 3_

2.5- Risk and confidence

Significance level is the risk taken in being wrong. Thus a significance level of5% means that in the long run the conclusion may be wrong 5 times out of 100.The following relation illustrates this concept.

Risk = 1 Confidence

To illustrate this concept more clearly, let us take the foregoing examples of

determining the compressive strengths of limestone for mining design purposes.For limestone we have found:_

X= 825 kg/cm2

S = 58.5 kg/cm2

Now if we base our mining design for compressive strength SX 2_

, we havetwo values; namely the upper and lower design limits;Compressive strength = 825 2S= 942 and 708 kg/cm2

3939


40/174

Since SX 2_

for this example cover 95% of the experimental values, then weare confident 95 % that taking a value between the lower and the upper limits asthe compressive strength bears 5 % risk.Risk = 1 0.95 = 0.05.By taking these values, we are 95 % sure that the rock behavior falls withinthese limits.

Risk is inevitable in everything we do. There may be usual risks that are almostinevitable, for example, the risk that a member of the project team is sick for

part of the project. There may be some unlikely but high impact risks, forexample the risk that the occurrence could cause the destruction of theorganization.

The project manager is responsible to constantly assess the risks and take actionneeded. There are three possible outcomes for each risk:

Take action now to avoid the risk, to reduce its likelihood, or to reduce itsimpact,

Make contingency plans so that the project team is ready to deal with theimpact and mitigate the risk if it occurs,

Agree that it is an acceptable business risk to take n action and hope thatthe risk does not occur.

The process of managing risks is:

Identify all realistic risks Analyze their probability and potential impact Decide whether action should be taken now to avoid or reduce the risk

and to reduce the impact if it does occur Where appropriate, make plans now so that the organization is prepared todeal with the risk should it occur

Constantly monitor the situation to watch for risks occurring, new risksemerging, or changes in the assessment of the existing risks.

40

Apply avoidance orreduction

Monitor &manageIdentify

risk

Analyzeprobability andimpact

40


41/174

Figure 16- The actions in risk management

In assessing risks the basic formulation given below can be applied:(Probability of the risk) X (cost if it happens) = (expected cost from the risk)

Equally simple is the rationale to apply when considering avoiding actions: ifthe cost of the avoiding action is less than the reduction in the expected cost ofthe risk then it is worthwhile.

Table 11- Quantifying risks and justifying avoidance actions

Probability 0.5x Financial impact $ 10.000 x

= Expectation of losses $5.000$5.000

Cost of avoidance or riskreduction $ 2.000 $ 2.0

Probability after effect ofAvoidance/reduction actions

0.1

x Financial impact after effect ofAvoidance/reduction actions

$ 10.000x

= Revised expectation of losses $1.000 $1.00

Net benefit from actions $2.00

41

Define contingency

plans

41


42/174

Note that you can reduce the expected cost of a risk either by reducing itsprobability, or by reducing its impact.

This guidance is mathematically sound, but there are several practical problemsrelying solely upon logic, for example:

The expected cost of a risk is, in effect, an average cost over a largenumber of projects, but in any one project a given risk either occurs or itdoes not. You either loose $ 10.000 or nothing- you never lose theexpected $ 5.000.

How much value do we place upon such things as survival of thebusiness, visible quality of the solution, and the reputation of theorganization?

How do we value human life and suffering (consider the case of buildinga system that keep the aircraft in the sky, or keep patients alive)?

What if the risk does not affect you but affects someone else such as athird party contractor?

How do we deal with very big and very small numbers?

Risk management should be seen as a continuous process throughout the project.Once the initial risk register and procedures have been established the Project

Manager, Project office staff, and all other project participants should be alertfor new, changing or occurring risks. Procedures for reporting risk should be aseasy as possible. Feedback from all participants should be encouraged andrewarded.

The Project Office would normally review the risk register proactively onregular basis. They would check the status of potential issues, for example,calling the responsible party and checking if there has been any change in thestatus. The Project Manager should also review the register on regular basis and

take actions as required. Information on risks would be reported to theleadership along with the other performance data.

2.6- Regression and correlation

A question often asked about a pair of variables x and y is, How do changes inx affect the value of y For example, as a man ages five years, how will thisaffect his blood pressure? Or we might ask a related question What is theexpected value of y for a certain value of x?

4242


43/174

A regression problem considers the frequency distributions of one variable whenanother is held fixed at each of several levels. A correlation problem considersthe joint variation of two measurements, neither of which is restricted by theexperimenter.

Examples of regression problems can be found in the study of yields infloatation with different amounts of reagents used, the hardness of metals, whichare heat-treated for different period of time or temperatures, the optimumnumber of trucks allocated for an excavator with varying dumping distances. Inthese problems the variation in one measurement is studied for particular levelsof the other variable selected by the experimenter.

When a variable is studied as a function of a single variable as Y= f(X) , this is aSimple Regression Analysis. Here Y is the dependent variable and X is theindependent variable.

When a variable is studied as a function of several variables as Y= f (X,Z,Q,.)this is called a Multiple Regression Analysis.

The variation parallelism between independent variable and the dependentvariable is called correlation. The measure for the degree of variation

parallelism is the coefficient of correlation. Measure, which shows thenumerical variation relation between variables, is the coefficient of regression.

The relation between variables can be either linear or non linear.

2.6.1- Simple linear regression

If x and y have a relationship with each other, in order to predict y from x wehave to be able to find a model for the relationship. The simplest model for arelationship is a straight line. If a straight- line model is appropriate, the line iscalled the regression line and we say that we are regression y on x. This type of

regression is called simple linear regression; simple indicates that there is onlyone independent variable, and linear indicates that the model is a straight line.

The linear relationship between the two variables is as follows:

Y = a + bX

Here,Y= Dependent variable

X= Independent variableb = Regression coefficient showing the variation in Y as a change in X

4343


44/174

a = Value for Y when X=0.

The unknowns in the above equation can be calculated by the following twoequations.

XbNaY

XbXaXY 2

Instead of real values of Y and X we can use the deviation of the arithmeticalmeans of the variables.

Where; Y=Average value of the dependent variable,X= Average value of the independent variable.

__

XXbNaYY

2____

XXbXXaYYXX

Since the sum of the deviations of the arithmetical means is zero, from the first

equation a=0, and the second equation can be expressed as follows:

2_

__

XX

YYXX

b

Here b is the regression coefficient.To find a we can use the following relation

__

XbaY or

_

XbYa

The simple linear correlation coefficient is:

4444


45/174

2_2_

__

YYXX

YYXX

r

The value of correlation coefficient varies between +1 and 1. Correlationcoefficient, which is very near to +1 shows a very strong variation parallelism inthe same direction, i.e., as y increases x increases also. Correlation coefficient,which is very near to 1 shows a very strong variation parallelism in theopposite direction, i.e., as y increases x decreases. Correlation coefficient, whichis very near to zero shows that there is no correlation between variables, i.e., anincrease or decrease or a variation in the dependent variable cannot be related tothe variations in the independent variable.

The square of correlation coefficient, r2, which is called The DeterminationIndex, is a meaningful measure in statistics. In regression analysis it isfrequently the first statistic, which is computed in order for the experimenter todetermine whether a regression equation will be useful for predicting y.Determination index, (r2), explains to what degree the variation in independentvariable, (x), can explain the variation in the dependent variable, (y). Forinstance, a value of 0.98 for r2 means that the variations in independent variablecan explain %98 of the changes in the dependent variable.

Let us consider the following problem where the project engineers are toestimate the cost of production of the ore, where a new development level is to

be driven in an existing underground mine. Since the ore is being extracted fromvarious levels, the cost of production data is available. The question is toestimate the cost of production at the 600 m. level.

Table 12- Variation of cost of production against depth of extraction

Production cost of ore-Y-($/ton)

Depth of extraction-X-(meter)

23.0 38026.1 40527.3 41628.8 43030.8 47032.5 500

Plotting the dependent and independent variables on a graph we see that relationis linear.

4545


46/174

Figure17- Relation of cost to depth

For linear relation we have the equation:

4646


47/174

Y= a + bX_

Y= 168.5/6 =28.1_

X= 2601/6 = 433.5

2_

__

XX

YYXX

b

= 0.075

_

XbYa

= -4.4

Thus the regression equation is:

Y= -4.4 + 0.07 X

The cost of production at the planned 600 meter level is estimated bysubstituting 600 for X, which is Y600=37.6 $/ton.

Now let us determine the correlation coefficient to check whether, the variationin the cost of production, (Y), is affected by the depth of extraction (X) or ourhypothesis is relevant.

2_2_

__

YYXX

YYXX

r

= 7.57x8.9747

9.735

,

r=0.98Which is a strong correlation, proving that the cost of production increases withthe depth of extraction.

47

no

Y

_

YY2_

YY

X

_

XX2_

XX

_

YY

_

XX

1 23.0 -5.1 26.0 380 -53.5 2862.3 272.9

2 26.1 -2.0 4.0 405 -28.5 812.3 57.0

3 27.3 -0.7 0.5 416 -17.5 306.3 12.3

4 28.8 +0.7 0.5 430 -3.5 12.3 2.5

5 30.8 +2.7 7.3 470 +36.5 1332.3 98.6

6 32.5 +4.4 19.4 500 +66.5 4422.3 292.6168.5 0 57.7 2601 0 9747.8 735.9

47


48/174

2.6.2- Multiple linear regression

Here we will consider the dependent variable as a function of two or moreindependent variable. Of course the relation between dependent variable and the

independent variables must be linear. The computation is straightforward, butstill tedious for large data sets and for measurement variables containing a largenumber of digits. Here we will illustrate it with small data sets consisting ofvariables measured as small integer values. Such data would be unrealistic formost studies involving multiple regression analysis, but they are suitable fordemonstrating the computational techniques, which are employed and therebydispelling some of the mystery, which many experience upon first examinationof the computer output for multiple regression analysis.

Thus for a regression relation involving two independent variables we have thefollowing equation:

Y = a + b1 X1 + b2 X2

Suppose our data set consists of (X1) and (X2) as independent variables and (Y)as dependent variable. Here it would be necessary to mention that the units ofX1, X2 and Y may be totally different like; average air temperature in C0 , airflow in m3/min and pressure in Pascal.

Table 13- Variables for multiple linear regression

Y X1 X2108 34

129 43126 49149 58168 64161 73174 78

We want to know whether we can detect a significant linear relationshipbetween X1 and Y and similarly to determine whether there is a linear

relationship between X2 and Y. However, we do not perform two simple linearregression analyses, because the results could be misleading if there is a relation

4848


49/174

between X1 and X2 . Therefore we solve a set of linear equations for a, b1 and b2which will take into account any possible linear relationship, termed co-linearity,

between the two independent variables X1 and X2. Three equations for theunknowns are:

_

22

_

11

_

XbXbYa . .(1)

__

112

_

2

_

112

2_

111 YYXXXXXXbXXb (2)

__

22

2_

222

_

11

_

221 YYXXXXbXXXXb.(3)

We first compute 1X =399 2X =385 Y =1,015 21XX =22,521

2

1X =24,279, 2

2X =21,565, 2

Y =150,803, YX 1 =60,112_

1X =57

_

2X =55_

Y =145 YX 2 =56,518

and find

nXXXXS /212

1

2_

1111

=1536

nXXXXXXXXS /2121_

22

_

1121

=576

nXXXXS /222

2

2_

2222

=390

nYXYXYYXXSy

/11__

111

=2257

nYXYXYYXXSy

/22__

222

=693This gives three the equations to solve the unknowns

a= 145 57b1 55b21536b1 + 576b2 = 2257

576b1 + 390b2 = 893

4949


50/174

The last two equations can be solved simultaneously, yielding; b1 = 1.37,b2 = 0.27, and substituting b1 and b2 in the first equation we find a = 52.23 .

Thus our multiple linear equation is:

Y = 52.23 + 1.37 X1 + 0.27 X2

The reliability of the regression equation is very commonly measured by the

multiple correlation coefficient. The multiple correlation coefficientyy

Ror R

can be thought of as the correlation between the observed Ys and the

Ys

predicted by the regression equation. For multiple linear relation correlationcoefficient is as follows:

2_2_

__

YYYY

YYYY

R

Unlike the situation for simple correlation, however, 0

R

1, because it wouldbe impossible to have a negative correlation between the observed and thepredicted values. The square of the multiple correlation R2 can be interpreted asthe proportion of the variability that has been accounted for by the regressionequation. R2 is between 0 and 1. If the equation fits the data well R2 is close to 1;if the linear model is a poor fit, R2 will be close to 0.

2.6.3- Non- linear regression

The relation between variables might be non- linear like the following equationand figure:

K = mqa

5050


51/174

Figure 18 Set of related pairs of values and

the regression curve

The above equation is a regression relation with one variable and is solved byfinding the values of m and a, which give the best fit. To solve the equation wehave to linearize the function:

K= mqa

Log K = a log q + log m or more generally,

Y = a X + cNow since we have linearized the function the solution for the regressionfunction can be obtained as explained under article 2.6.1.

In the case of a non-linear regression with two variables, K = m qa Lb , thesolution is simple, because the functions of the above form can be readilylinearized.

Log K = a log q + b log L + log mor more generally ;

X1 = a X2 + b X3 + cSince we have linearized the function the solution for the multiple non-linearfunction can be obtained as explained in article 2.6.2. In order to express therelation in the form, K = m qa Lb , anti-logarithm of the unknowns (a, b, c)should be taken.

In regression analysis especially when dealing with more than one independentvariable and non-linear relations statistical computer packages are recommendedto be utilized.

3- PRESENT AND FUTURE MARKET TRENDS

5151


52/174

3.1- Introduction

All industrial projects presuppose a minimum level of production below which it

is uneconomic to produce the commodity. Before any detailed study of a projectis undertaken, it is essential to have at least a rough idea of the size of the marketin question. Only if the anticipated volume of demand (locally and possibly forexports) can be assumed to be above a certain minimum level, it is possible to

begin exploring the technical feasibility of the project. Experience shows that agreat many projects have had to be abandoned because the market did not comeup with the forecast, or simply no forecasts had been made.

The concept of a market should be interpreted very widely. It should include thewhole environment in which the enterprise is to live and to which it must adaptitself: consumers, suppliers, competitors and all kinds oftechnical, material,political, legal and administrative restrictions. An enterprise cannot operateunless it has been created for a specific market, and, once created, it cannotcontinue working unless it constantly adapts itself to the changing market.

3.2- Analyses of past and present demand

Analyses of past and present demand calls for the collection of quantitative andqualitative information about the market for the goods considered.

Here two questions arise: What are the main categories of data to be collected? Where they can be obtained?

The first question concerns the aim of the analyses where the second questionconcerns the period for which data must be collected. To analyze the market forthe product in question we may need to collect statistical data from reliablesources. Such sources are readily available in Turkey. Following sources may benoted:

State Institute of Statistics ( Devlet statistik Enstits DE ) Central Bank of Turkey (Merkez Bankas) Department of Treasury and Commerce ( Hazine ve Ticaret Mtearl) Chamber of Commerce and Industry of Turkey (Trkiye Sanayi ve Ticaret

Odalar) Union of Chamber of Turkey (Trkiye Odalar Birlii) State Planning Organization (Devlet Planlama Tekilat DPT ) Ministry of Industry (Sanayi Bakanl)

Ministry of Transportation ( Ulatrma Bakanl) Ministry of Construction (Bayndrlk Bakanl)

5252


53/174

Ministry of Energy and Natural Resources ( Enerji ve Tabii KaynaklarBakanl)

Ministry of Employment( alma Bakanl)

The length of period chosen will depend on two factors, the first of which will inmany cases be decisive. The period for which homogenous statistics are available, i.e., during

which data have been collected following the same rules. Factors, which may have appreciably modified the trend of demand for

the products e.g., economical crises, substantial change in custom dutiesor quotas.

3.2.1- Quantitative information

3.2.1.1- Information relating to physical quantities

Information relating to physical quantities consists mainly of statisticsconcerning production, imports, exports, and possibly variation in stocks.

Actual consumption of a good (or effective demand) can be calculated asfollows:

Consumption= Production + Imports Exports Increase in stocks

These statistics can be collected on national basis to permit internationalcomparison, similar work will, if possible, be done for other suitably selectedcountries.

Table 14- Data to compute the consumption of a certain good (tons)

Years Production Imports Exports Increase instocks

2000 1,500,000 1,000,000 - -2001 1,750,000 1,000,000 - 80,0002002 1,900,000 500,000 350,000 150,0002003 2,300,000 500,000 380,000 250,0002004 2,800,000 1,500,000 - 100,0002005 3,200,000 1,700,000 - 50,000

Thus the consumption of the good is as follows:

5353


54/174

Table 15- Consumption of the good

Year 2000 2001 2002 2003 2004 2005

Consumption 2,500,000 2,670,000 1,900,000 2,170,000 4,200,000 4,850,000

3.2.1.2- Statistics related to prices

Time series of prices as well as physical quantities of the same period of timemust be collected, preferably from the same source.

Average wholesale prices during the same period, Average retail prices during the same period,

can be used as an indicative for prices.

3.2.2- Qualitative information

There are numerous kinds of qualitative information. Such information can beobtained by studying the three following factors among others.

Methods of distribution and marketing of product, Attitude of customers, Government action in respect of a product.

3.3- Different methods of estimating future demand

There are many possible means of estimating future demand. In some cases asimple study of import statistics, possibly backed up by a survey among localconsumers, will give a fairly clear idea of the size of the future market; in othercases it may be necessary to purse the investigation further, possibly usingadvanced econometric techniques. Between the two extremes there exists awhole range of m

project management in mining-revised

Documents