HOW TO BECOME A WINNER?

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HOW TO BECOME A WINNER?

IMPROVING MEDUSA’S AIRBORNE GAMMA SPECTROMETERS

by:

TIMON SYBOUT VAN RIJS University of Groningen Faculty of Economics and Business Master Thesis – Technology Management

October 2011

First supervisor: ir. J.P.C. Wubben

Second supervisor: prof. dr. ir. G.J.C. Gaalman

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I. Preface

This master thesis is the last part of my study Technology Management at the University of Groningen. I can say that I had five informative and enjoyable years while studying in Groningen. Particularly working on this thesis was very informative, and I am very grateful to everyone who helped me with it.

When dr. J. Limburg asked me to do this research, at first, I had no idea how extensive this research would be. Although if you consider it afterwards, a service-oriented company (Medusa), with almost no sales experience, wants to sell an innovative survey system in an unknown market (i.e. mining industry) for Medusa. A technology manager will instantly notice a number of challenges.

In the first paragraph I thanked everyone who helped me, but some of them need to be emphasised. Starting with Medusa, this company offers a pleasant working environment and a superior learning environment. I think both are primary originating from the employees of Medusa. This learning environment is in my opinion the real strength of Medusa. All employees want to research, learn and share knowledge. I could always ask them for help regarding my research or discuss my research methodology with them. I want to thank all employees of Medusa for this. In particular dr. J. Limburg who helped me when I had questions about the product or the used techniques. Next to that, he helped me with collecting my data. A very special thanks goes to dr. R.L. Koomans, who supported me a lot during my thesis. We discussed many times about this research, he motivated me, and he had always useful advices.

Finally, I would like to thank ir. J.P.C. Wubben, my supervisor from the University of Groningen. It was very pleasant working with him. Every time we had a meeting, he had useful feedback and constructive ideas. Next to Wubben, I would like to thank prof. dr. ir. G.J.C Gaalman as my second supervisor of the university.

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II. Abstract

Medusa Explorations is specialised in geophysical surveys, and is using primarily gamma spectrometry. For this type of surveys Medusa developed a gamma spectrometer. Besides surveys, the management of Medusa wants to sell their gamma spectrometer in the mining industry.

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III. Table of Contents

I. Preface ... 2

II. Abstract ... 3

1 Introduction... 6

1.1 Medusa Explorations B.V... 6

1.2 Medusa Airborne Survey System ... 7

2 Research design ... 8 2.1 Research objective ... 8 2.2 Problem analysis ... 8 2.3 Conceptual model ... 10 2.4 Research questions... 14 2.5 Thesis arrangement ... 15 3 Background information ... 17 3.1 Gamma spectrometry ... 17 3.2 Market description ... 20

3.3 Prospectors and Developers Association of Canada Convention ... 21

3.4 Customer description ... 21

3.4.1 Tundra airborne surveys ... 21

3.4.2 Precision GeoSurveys Inc. ... 22

3.4.3 Geotech Ltd. ... 22

3.4.4 Novatem ... 22

3.4.5 Fugro Airborne Surveys ... 23

3.4.6 Sander Geophysics ... 23

3.4.7 SkyTEM ... 24

3.4.8 TerraScan ... 24

3.4.9 General ... 24

3.5 Competitors description ... 25

3.5.1 Radiation Solutions Inc. ... 25

3.5.2 Pico Envirotec Inc. ... 26

4 Constructing an instrument for measuring performance ... 27

4.1 Performance objectives ... 27

4.1.1 Gamma spectrometer ... 28

4.1.2 Logger software ... 30

Data analysis software ... 31

4.1.3 Costs ... 32

4.1.4 Response time and dependability ... 33

4.1.5 Flexibility ... 34

4.1.6 Reputation of supplier ... 35

4.2 Sub conclusion ... 36

5 Measuring the current performance ... 37

5.1.3 Data analysis software... 39

5.1.4 Costs ... 40

5.2 Sub conclusion ... 43

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6.1 Importance-performance matrix... 44

6.1.1 The ‘Appropriate’ zone ... 46

6.1.2 The ‘Improve’ zone ... 46

6.1.3 The ‘Urgent Action’ zone ... 46

6.1.4 The ‘Excess?’ Zone ... 46

6.2 Performance against competitors ... 46

6.3 Importance for customers ... 47

6.4 Analysing the importance-performance matrices ... 48

6.4.3 Data analysis software... 50

6.4.4 Costs ... 50

6.5 Sub conclusion: Ranked list of indicators ... 53

7 Improvement-investment costs matrix ... 55

7.1 Improvement-investment costs matrix ... 55

7.2 Investment costs of improvements ... 56

7.2.1 Resolution (spectrometer) ... 56

7.2.2 Max count rate (spectrometer) ... 57

7.2.3 Robustness (logger) ... 57

7.2.4 Real-time spatial data plotting (logger) ... 57

7.2.5 Integration with Geo Software (analysis) ... 57

7.2.6 Compliance to standards (reputation) ... 57

7.2.7 Compatible with DAQ systems (spectrometer) ... 58

7.2.8 Known in market (reputation) ... 58

7.2.9 Real-time nuclide concentrations (logger) ... 58

7.2.10 Number of spectrometers sold (reputation) ... 58

7.2.11 Multiple analysis methods (analysis) ... 58

7.2.12 Years experience (reputation) ... 58

7.2.13 Responsiveness quotation request (response) ... 59

7.2.14 Internal backup (spectrometer) ... 59

7.2.15 Quality of support (response) ... 59

7.2.16 Reliability of promised lead times (response) ... 59

7.2.17 Responsiveness of support (response) ... 59

7.2.18 Flight guidance (logger) ... 59

7.2.19 Overview of investment costs ... 59

7.3 Plotting the improvement-investment costs matrix ... 60

7.4 Sub conclusion ... 61 8 Conclusions ... 63 8.1 Conclusions ... 63 8.2 General applicability ... 64 8.3 Discussion ... 65 8.4 Further research ... 65 References ... 66

Appendix 1: Explanation of technical terms used ... 68

Appendix 2: Performance objectives ... 70

Appendix 3: Current performance ... 73

Appendix 3: Customer importance survey ... 74

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1 Introduction

1.1 Medusa Explorations B.V.

Medusa Explorations B.V. (Medusa) is a service oriented organisation, which is specialised in the use of geophysical tools for mapping sediment and soil composition/pollution. Medusa is primarily using a technique called gamma spectrometry. With this technique, naturally occurring radioactivity is measured in order to reveal soil information. Apart from indicating sources of uranium (i.e. radioactive), gamma spectrometry can also determine the composition and presence of minerals and other precious metals, above and below the (water) surface. For these surveys Medusa has developed their own gamma spectrometer.

Medusa was founded in the year 2000, by dr. J. Limburg and dr. R.L. Koomans. Both received a PhD at the University of Groningen on studies related to gamma spectrometry. After their PhD they started Medusa as a spin-off project from the Institute of Nuclear Physics (in Dutch: Kernfysisch Versneller Instituut) at the University of Groningen. After several years the university has sold their shares, and Medusa is now owned by three shareholders, Tauw B.V. and Koomans and Limburg. Currently ten employees are working at Medusa. All with different backgrounds, for example geologist, surveyors and engineers.

In the beginning, Medusa was focused on doing surveys in lakes, rivers, seas and harbours. These surveys aimed on mapping the contamination of sediments due to heavy metals and organic compounds (e.g. PCBs). This information is very valuable from an environmental and economical point of view. Health risks associated with these pollutants may restrict activities like fishing and recreation. Moreover, to maintain access for shipping, most waterways and harbours are dredged regularly. An important element of dredging is the disposal of the dredged sediments. There is a large (financially) difference between the disposal of contaminated and non-contaminated sediments. (Van der Graaf, E.R., Koomans, R.L., Limburg, J., and De Vries, K., 2006)

Figure 1, Classification of dredge at Farmsum

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7 Figure 1 is reported to the customer. The objective of this survey was to classify the dredging in three groups of contamination.

Next to the mapping with a gamma spectrometer, Medusa provides a lot of related services. For example, mapping contamination on land and searching for pipes and wires using a ground penetrating radar. Medusa is doing geophysical research for: archaeology, dredging, engineering, environmental and mining.

1.2 Medusa Airborne Survey System

Medusa is using gamma spectrometry over ten years, now. In these years Medusa developed a lot of knowledge, a gamma spectrometer and software applications. Medusa wishes to generate additional revenues from these developments by selling survey systems. So, besides doing surveys, they also want to sell products.

This survey system is called the Medusa Airborne Survey System (MASS). MASS consist of four main parts and these in are, along their interconnections, shown in the grey boxes Figure 2. Next to the gamma spectrometer, Medusa developed two software applications. Namely, a data logger and GAMMAN (analysis software). The data logger is connected with the gamma spectrometer by a data cable. The logger software makes sure all measurements from the gamma spectrometer will be written to measurement files. After the survey, the analysis software will read these measurement files. The analysis software can extract information from all these measurement data. With this information, reports and maps can be created. To execute this analysis correctly, a standard spectrum is required. A standard spectrum is the fourth part of MASS. Medusa has an calibration

facility, here an initial sensor calibration can be preformed. This calibration results into a standard spectrum, and this will be used by the analysis software.

This comprehensive solution is called: MASS (a measurement tool, software and calibrations). Medusa started selling MASS, in the year 2009. This selling is done in a separate department, called Medusa Systems. Medusa Systems has chosen to target the mining industry with a light weight gamma spectrometer. This industry is chosen, because the gamma spectrometer could be very useful to discover new minerals or precious metals. The objective is; to use the same techniques used for dredge mappings (mentioned earlier) in the mineral exploration. The boat will be replaced by an airplane with a gamma spectrometer mounted on it. By using special analysis methods on the survey data, potential mining spots can be found. The use of a gamma spectrometer in a small airplane, mean that large areas can be scanned relative easily. The management of Medusa expects that their unique selling point is in decreasing the size and weight of gamma spectrometers. This will satisfy the request for smaller systems which can be used in smaller and cheaper planes.

This concept sounds promising, however we will see, during the problem analysis, that the sales are unsatisfactory. The management of Medusa obviously wants to locate and solve the causes of these disappointing sales.

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2 Research design

2.1 Research objective

To make sure this research and the results are valuable to Medusa, the objective of this research should be made clear. De Leeuw (1996) stated that a research objective should answer the following three questions:

1. Who asked for the research?

2. What is their desired end-product (knowledge)? / What should be solved in the end? 3. Why is this important for them?

In 2009 Medusa started selling MASS. Despite the effort of a dedicated salesman, the sales are falling short. Customers who would like to buy a gamma spectrometer, do request quotations at Medusa and at Medusa’s competitors. However, the customers choose the spectrometers of the competitors, and they accept the quotations of the competitors. The management of Medusa and the salesman are thinking (i.e. the presumption of the client) that the following is the problem: the gamma spectrometers of the competitors are perceived to be better by the market. The first question of De Leeuw (Who asked for the research?), can be answered now. Namely, the management of Medusa asked for this research.

Now the “real” problem must be defined, afterwards we can answer the other two questions of De Leeuw.

2.2 Problem analysis

“He who defines the problem, defines the solution.” - Bob Baxley.

The citation of Bob Baxley reveals his opinion regarding a carefully executed problem definition. De Leeuw presumably shares this opinion. His Diagnose, Design and Change method (DDC-Method) prescribes an extensive problem analysis, which is the foundation for an applicable solution to a problem. In this problem analysis the DDC-method will be a guidance.

The first phase is the Diagnose phase. The objective of this phase is to find the main problem statement. This will be the output of Diagnose phase. The input of this phase is the presumed problem of the client. Possibly, this is not the real problem the client is concerned about.

Properties of the system

System Output

Properties of the output

Instrumental complaints

Functional complaints can (possibly) cause

are caused by

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9 There are two types of complaints defined in the Problem Owner Analysis, this analysis is a part of DDC method. These complaints are: Instrumental complaints and functional complaints. Instrumental complaints are; complaints about the properties of the system. Functional complaints are; complaints about the output. Instrumental complaints can cause functional complaints. This is shown in Figure 3. An example will clarify this even more.

A factory manager complains that his workers at the assembly line are working very messy. (instrumental complaint) He asks how he could change this.

However, after an interrogation with the manager, it becomes clear that the real problem is the quality of the products. A lot of customers return defect products. Thus, the real complaint of the manager is that the factory is producing too many defects. (functional complaint) The factory manager concluded that the defects are caused by the messy workers. This could be possible, but is not necessary the main cause. The primary cause could be, for example, the bad quality of the input.

This example shows the importance of defining the ‘real’ problem (i.e. functional complaint). If in the example the instrumental complaint was solved, the factory could still produce too many defects, due to the bad quality of the input.

Now that we clarified the differences between instrumental and functional complains, we can return to the complain of the management of Medusa. That is: the gamma spectrometers of the competitors are perceived to be better by the market. On the highest aggregation level (i.e. the market as a whole), this is a complain about a property of the system, which means it is an instrumental complaint.

This instrumental complaint could cause the functional complaint, disappointing sales of MASS. This is the ‘real’ problem the management of Medusa is concerning about. Besides, the management of Medusa concur that this is the ‘real’ problem they would like to see solved. And this is the answer on De Leeuw’s second question (What should be solved in the end?). The management of Medusa wants to have an advice on what they have to change in order to increase the sales of MASS. In the next chapter we create a conceptual model, herein the ‘sales of MASS’ has a central role.

But first the last of the three questions of De Leeuw (1996), namely, why is this important for them? For Medusa this research is important, because a lot of resources have been invested in the development of the gamma spectrometer and these investments should be earned back. Luckily, the investments on design and development are partly earned back, because Medusa is using the spectrometer for their own survey work. Yet, there is a potential second pay out.

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2.3 Conceptual model

During the creation of the conceptual model, we will:

 Define the focus of this research;

 Discover possible directions for a solution; and

 Find the controls which can be influenced in order to increase the sales of MASS. In the following conceptual model (shown in Figure 4) there is a central role for ‘sales of MASS’. Sales of MASS: The number of sold survey systems. At this moment, Medusa sold only one survey system. The main objective of this research is to increase this number. The variable sales of MASS has a strong relation with the profit from MASS.

Profit from MASS: Medusa wants to increase their profit from MASS. At this moment, the department Medusa Systems is not profitable. Logically, the management want to change this. The profit from MASS is positive related to the total sales of MASS and positive related to the selling price of MASS. And, in contrast, negatively related to total cost. All these three relations could be explained by the following profit formula (Begg, D., and Ward, D., 2004):

One could expect that profit from MASS is the main variable in this research. Obviously, the management of Medusa want to improve the profit from MASS, however, that is not where the real problem lies. The marginal profit is acceptable, but without any sales there will be no profit at all. To narrow the scope, in this research there is chosen to first try to increase the sales of MASS. An increase in sales will lead to an increased profit. This is the first step (i.e. this thesis). Afterwards, additional research can be conducted in order to maximize profit.

Sales of MASS Product advantage

+

Selling price of MASS

-Medusa’s performance Competitors’ performance Performance of MASS Performance of competitors’ products

-

+

-+

+

Market demand

+

Profit from MASS

*

= Controllable Total cost

*

-Figure 4, Conceptual model

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11 is not a part of this research. Since, Medusa only sold one survey system, a decrease in the production cost will not increase the profit. Nevertheless, such a research can be valuable when the sales are enhanced.

Selling price of MASS: The selling price of MASS, consists of the price of a gamma spectrometer, the logger software, the analysis software and an initial calibration. A higher selling price means a higher marginal profit, which is in the model the positive relation between selling price of MASS and profit from MASS. On the other hand there is a negative relation between selling price and sales of MASS. This relation is underpinned by the law of demand. The law of demand states: As the price falls, consumers are willing to demand greater amounts of the good and vice versa (Begg, D., and Ward, D., 2004). There are some exceptions (i.e. Giffen goods and Veblen goods), where the law of demand not applies.

There is no reason to assume that in this market the law of demand does not apply. In general, customers are seeking for the best quality for the lowest price. However, when MASS is priced too cheap it can have a negative effect on the perceived quality of the product.

Since, Medusa determines the price of MASS, the selling price is very good controllable, shown by the (*) in the conceptual model.

Product advantage: Product advantage is defined as the superiority and/or differentiation over competitive offerings (Henard, D. H., and Szymanski, D. M., 2001). Meta-analysis conducted by D. H. Henard and D. M. Szymanski (2001) shows that the variable product advantage has a significant positive relation with the sales of products. This gives scientific support for the obvious relation between product advantage and sales of MASS.

In this thesis product advantage consist of the following:

 The performance of MASS (positive related);

 The performance of gamma spectrometers from the competitors (negative related);

 Medusa’s performance, as a company (positive related); and

 Competitors’ performance (negative related).

This means that the product advantage is shaped by the performance of the product, and the company. The product performance (i.e. performance of MASS and performance of competitors’ spectrometers) is mainly assessed by the specifications of the product. And the company performance is primarily assessed by the properties of the organisation.

Before a customer purchases a gamma spectrometer, they will extensively compare the available options on all aspects. During this selection the product specifications as well are important, but subjective factors will also be taken into consideration. Some examples of these subjective factors are: quality of support and known in the market. These soft factors can be decisive, particularly when the products specifications are almost equal.

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12 As shown in the conceptual model, a higher/better performance of MASS will result into a higher product advantage.

Performance of competitors’ products: The product advantage of MASS is not only defined by the specifications of MASS, but also by the specifications of the competitors. For example, when a competitor improves their gamma spectrometer, in a status quo, this means that the product advantage Medusa has decreases.

Medusa’s performance: This is the performance of Medusa as a company. Thus, the ‘specification’ of the company. For example, years experience and quality of support. As said before, these factors can be decisive in a purchase decision, and for that reason it has a positive relation with product advantage.

Competitors’ performance: The relation between Medusa’s performance and the competitors’ performance is comparable to the relation between the performance of MASS and the performance of competitors’ products. This is the performance of the competitors, and negatively influences the variable product advantage.

Market demand: The last variable is the market demand, and this variable negatively influences the sales of MASS. A decrease in the demand for spectrometers will result into a decrease in sales. In the last years there were very disappointing developments in the mining industry, which is the main market for MASS. One of the largest metals & mining industries is the Canadian metals & mining industries. So, observations from the Canadian mining industry will certainly have global influence. A report from Datamonitor about the Canadian metals & mining market outlines the following: “The Canadian metals & mining market experienced strong growth until 2009 when it fell into a steep decline. The industry shrank by 36.6% in 2009 to reach a value of $30.6 billion.” (Datamonitor, 2010)

Figure 5, Canada metals & mining industry value (Datamonitor, 2010)

And: “The metals and mining industry was greatly affected by a global drop in commodity prices in 2009 which caused a sharp decline in many markets.” (Datamonitor, 2010)

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13 accelerate, with an anticipated compound annual growth rate (CAGR) of 12.3% for the five-year period 2009-2014, which is expected to drive the market to a value of $54.6 billion by the end of 2014.” (Datamonitor, 2010). When this recovery is really coming, it is important for Medusa that they improved their gamma spectrometer, in order to fully profit from this market recovery.

In the following table all variables of the conceptual model are shown again, along the degree of controllability for Medusa. Medusa wants to improve both variables sales of MASS and profit from MASS, according to the conceptual model both variables can only be changed indirectly. In the third column the effectiveness of the variables is shown. This means, how effective is it to control this variable in order to influence the target variables (i.e. sales and profit). For example, when the total cost (good to control) are decreased this does not mean that the profit from MASS increase.

Table 1, Degree of controllability and effectiveness

For this reason we need to look for the next controllable variable, that is, the selling price. This variable is very good to control. Basically Medusa can change the selling price almost instantly. However, it is only effective when there are any sales. If so, finding the optimal selling price of MASS will result into maximising the profit.

On the other hand, Medusa could try to increase the demand of MASS by decreasing the selling price. Though, for the customers of spectrometers high quality is probably more important than the selling price. Besides, continuing this research with selling price will almost certainly result into an advice to decrease the selling price. This can lead into a too cheap product and everlasting damage to Medusa’s reputation.

Variable Degree of controllability Effectiveness

Sales of MASS Only indirect -

Profit from MASS Only indirect -

Total cost Good, trying to cut down costs. Good, but only when there are any sales

Selling price MASS Very good, determine a new price

Good, when there are at least sales.

Product advantage Only indirect -

Performance of MASS Good, invest in product Effective Performance of competitors’

products

No Effective

Medusa’s performance Good, change internally Effective

Competitors’ performance No Effective

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14 The third controllable variable is the performance of MASS, the conceptual model assumes that an improved performance means a higher product advantage, and this will lead to increased sales. Meaning that performance of MASS is both controllable and effective.

The subsequently controllable variable is Medusa’s performance. Also this variable positively influences the product advantage, which in the end will lead to increased sales.

Therefore, we will continue with Performance of MASS and Medusa’s performance. These two variables will return in the research questions.

2.4 Research questions

The conceptual model proposes that in order to increase the sales of MASS, the product advantage has to be increased. The same model shows that there are four variables (i.e. performance of MASS, performance of competitors’ product, Medusa’s performance and Competitors’ performance) which influence the product advantage. From these four variables the variables: Performance of MASS and Medusa’s performance are the two which are effective and good to control. Both will be used to shape the research question. Though, we will still use the external two variables to define the required improvements. From this research objective and the conceptual model the following research question is extracted.

Research Question:

Which product improvements and/or organisational changes should Medusa perform in order to increase the sales of Medusa’s Airborne Survey System (MASS)?

The performance of MASS is in the research question reshaped into product improvements, which are improvements on the complete survey system (a gamma spectrometer, logger software, analysis software and a calibration). Organisational changes are the changes/improvements related to Medusa as a company. These are not an integrated part of the product, but could be important for the customers. For example, quality of support or number of scientific papers published. In the conceptual model this is the variable Medusa’s performance.

To get an answer on the main research question, we divided it into four sub questions. The goal of the first sub question is to construct an instrument for measuring the performance of a supplier of gamma spectrometers. That is, on product performance and company performance. To be able to do this we have to find performance objectives. These performance objectives consist of a number of performance indicators. With these indicators the overall performance can be measured.

Sub Question 1:

How to construct an instrument for measuring the performance of a supplier of gamma spectrometers?

It is important to note: that we should not confuse the instrument from sub question 1 and the physically measurement tool (i.e. gamma spectrometer).

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Sub Question 2:

Using the instrument form SQ1, what is the current performance of the suppliers of gamma spectrometers?

After executing sub question 2, we have both measured the performance of Medusa and the performance of the competitors, we can compare these performances. This objective comparison should proof if this can be the cause of the disappointing sales. If so, this means that this research is heading the right direction. Besides, this comparison it is essential input for sub question 3.

To give Medusa an advice on which elements and in which order Medusa should improve these elements, the result of SQ3 will be an ordered list with improvements. The ordering is done considering the customers’ needs (i.e. customer importance) and the current performance. This leads to the following sub question:

Sub Question 3:

How to construct a ranked list of improvements, ordered by the current performance of MASS and customer importance?

In sub question 3 we use a technique which has some limitations. The cost to perform an improvement is not considered. However, this is crucial for a small company, with limited resources. This factor we are adding in sub question 4, this will give the following question:

Sub Question 4:

What should change in the ranked list of improvements (from SQ3), when the investment costs/effort of these improvements are considered as well.

As we said earlier, the management of Medusa should be helped when this thesis gives a well considered list of improvements they should execute in order to become an order-winner. This list should both be empirically and scientifically underpinned. The answer on sub question 4 will give such an ordered list.

2.5 Thesis arrangement

The following list shows the chapters in this thesis and provides a brief description of these chapters. 1. Introduction

Introduces Medusa and their problems according to MASS. 2. Research design

Defines the ‘real’ problem, and defines the research questions. 3. Background information

Information about gamma spectrometry, and the market environment. 4. Constructing an instrument for measuring performance

Constructing an instrument for measuring the performance of spectrometers and their suppliers.

5. Measuring the current performance

Measuring the performance of Medusa and their two suppliers, using the instrument from sub question 2.

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16 Unify the current performance of Medusa and the customers’ needs to assemble a ranked list of improvements. This is done using importance-performance matrices.

7. Improvement-effort matrix

Rearrange the previous list of improvements by including effort

Add the missing effort/cost to the ranked list, and rearrange the ranked list. 8. Conclusion

Give Medusa an advice on the improvements they should perform.

The following scheme (Figure 6) gives an overview of the arrangement of this thesis. Where on the left side the input of the research question is shown. And on the right is the corresponding research question shown. Technical terms used in this thesis, are briefly explained in appendix 1.

Problem:

Disappointing sales of MASS

Research question:

Which product improvements and/or organisational changes should Medusa perform in order to increase the sales of Medusa’s Airborne

Survey System (MASS)?

Sub question 1:

How to construct an instrument for measuring the performance of a supplier of gamma spectrometers?

Sub question 2:

Using the instrument form SQ1, what is the current performance of the suppliers of gamma spectrometers?

Sub question 3:

How to construct a ranked list of improvements, ordered by the current performance of MASS and customer importance?

Sub question 4:

What should change in the ranked list of improvements (from SQ3), when the investment costs/effort of these improvements are

considered as well. Customers Competitors Medusa’s performance Customers importance survey Competitors’ performance Medusa’s experiences Medusa’s estimations Performan ce

Ranked list of improvements

Conclusion

Answer to the Research Question

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3 Background information

Before we can answer the research questions, we have to examine necessary background information on the subject. This information is required to fully understand the intermediate steps and the conclusions. The following scheme shows the paragraphs which will be handled in this chapter. Customer description (Paragraph 3.4) Competitor description (Paragraph 3.5) Conference: PDAC (Paragraph 3.3) Gamma spectrometry (Paragraph 3.1) Market description (Paragraph 3.2)

Figure 7, Chapter arrangement

In this chapter the underlying techniques (i.e. gamma spectrometry) of MASS will be explained, first. Secondly, the target market of MASS will be described. A large part of my preliminary research about the customers and competitors, I did at the Prospectors and Developers Association of Canada (PDAC) convention in Toronto. This convention will be described in Paragraph 3.3.

Following with a description of the companies operating in this market, these are the (potential) customers (Paragraph 3.4) of MASS and the two competitors of Medusa (Paragraph 3.5).

3.1 Gamma spectrometry

In this research it is essentially to have a basic understanding of gamma spectrometry and of the underlying techniques.

A gamma spectrometer can measure very small amounts of radiation and give an energy spectrum of this radiation as result. But how does this work?

On the right there are two pictures of Medusa’s gamma spectrometer. In the figure 3 the end-product is shown, a painted aluminium case, with all the electronics inside. The second picture (figure 4) is an ‘exploded’ view, where the electronics (in front of the case) and the scintillation detector (on top of the case) are visible. These two components are the vital ‘organs’ of the gamma spectrometer, where in this analogue the scintillation detector is the eye, and the electronics are the brains.

Figure 9, Medusa's gamma spectrometer

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18 Figure 5 gives a schematic view of the scintillation detector. In this scheme the scintillation crystal and the photomultiplier tube are the basic components. Scintillation crystals are materials that produce light when ionizing radiation passes through them. These scintillation materials can be solid, liquid or gases. The following materials are commonly used: Sodium Iodide, Caesium iodide and Bismuth Germanate. The scintillation crystal used in MASS is made from Caesium iodide (CsI).

This and the other materials absorb gamma radiation mainly by one of the three absorbing mechanisms (i.e. pair production, the photo-electric effect and Compton scattering). An in-depth explanation of these principles is out of the scope of this research. However, globally they all work as following. The absorption of radiation is raising electrons to excited states. After the subsequent de-excitation, the crystal emits multiple visible photons. (Tijs, M., 2007; Van der Woude, A., and De Meijer, R., 2003)

The light (in the visible range) emitted from the crystal interacts with the photocathode of the photomultiplier tube (shown in Figure 11) releasing electrons. The photomultiplier tube is also visible in the previous Figure 10, right under the scintillation crystal.

The released electrons are guided, with the help of an electric field, towards the first dynode. The dynodes are coated with a material that emits secondary electrons. These electrons along the secondary electrons move towards the second dynode and so on, until the anode. On every step there is amplification, the final amplification can be 106 or higher. Due to the strong amplification it is possible to detect very low energy levels of radiation.

Figure 11, Photomultiplier tube

After the amplification, the energy on the anode will be measured by an Analogue-to-Digital Converter (ADC). The amount of energy determines where the radiation pulse comes into the spectrum. For example one gamma pulse with an energy of 1.5 keV will be placed as shown in Figure 12. Along with other pulses, with different energy values, they form an energy spectrum. In Figure 12 an energy spectrum with a resolution of 9 channels is shown, in the gamma spectrometry a much higher resolution is used, up to 1024 channels (Figure 13).

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19

Figure 12, simple energy spectrum Figure 13, full energy spectrum

Now that we understand the basics of how gamma radiation is amplified, converted to electric energy and put into a spectrum. The two mostly used methods of getting information (i.e. nuclide concentrations) from the spectra will be briefly outlined. The methods are the Window analysis and the Full Spectrum Analysis. Using the Window analysis one should draw virtually three windows in the spectrum (as shown in Figure 14, Window Analysis). These three windows correspondents with one of the following nuclides Potassium (40K), Thorium (232Th) and Uranium (238U). First the concentration in the Thorium-window will be determined. Secondly the Uranium concentration is determined. A part of the counts in the Uranium-window originate from the Thorium radiation. This part will be stripped from the Uranium-window and the surplus is the Uranium concentration. Finally, the Uranium and Thorium counts are stripped from the Potassium-window where the remaining determines the Potassium concentration. In fact, it is a system of three linear equations with three variables, which have to be solved. This way for all three nuclides a concentration can be estimated.

The Window analysis uses only three parts (i.e. the windows) of the spectrum. Since only a limited part of the spectrum being is used, this method often leads to results with relatively large uncertainties. (Hendriks, P.H.G.M., Limburg, J., and De Meijer, R.J., 2001).

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20 In contrast to the Window method, the Full Spectrum Analysis uses every channel of the spectrum. A least squares fit of all channels will be performed. An over determined system of equations (i.e. for every channel an equitation) with three unknown variables. For this method of analysis, the exact response of the detector for each of the nuclides has to be known, these are called the standard spectra. The last method is much more complex, but yield better results. Medusa’s gamma spectrometer uses, the more advanced, Full Spectrum Analysis.

3.2 Market description

To describe the customers and competitors, we first have to understand the structure and activities in target market. Medusa has chosen to target the mining industry. The mining industry consists of three main phases. Namely, exploration, development and

extraction, shown in Figure 16.

MASS can be used in the exploration phase, to locate resources. Therefore, the (potential) customers of MASS are the companies which operate in the mineral exploration phase. Mineral exploration can be divided into different steps. First, a land owner or government sells the right to explore, and mine minerals on a (large) area. In return, the buyer of these rights is obliged to really do explorations within a certain time.

The rights will be acquired by a prospecting company. They will do a rough exploration, and try to indentify hotspots (areas with indications of resources). This type of exploration is mostly performed from airplanes. This way a large area can be relatively

quick scanned. It is important to note that hotspots are spots with increased possibilities of resources, there is no certainty. Nevertheless, with these hotspots found in an area it will be much more valuable.

After finding hotspots, the prospecting company will hand over the exploitation rights to a junior mining company. This company will do in-depth research at the hotspots. They will do test drills to determine the characteristics of the hotspots. Among these are: its size, shape, and location with respect to the surface, as well as the mineral quality, distribution and the quantities. With this information calculations can be done to conclude if a hotspot is commercially viable. If so, the exploitation rights of that area will be once again passed to a senior mining company. These are the companies which have the capital and knowledge to construct mines. Prior to the construction, the senior mining companies will do more research and develop mining plans. (Bhappu, R.R.J., Guzman, J., 1995)

Figure 16, The mineral supply process (Mackenzie and Woodall, 1988)

Land owner Prospector Junior mining company

Mining company

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21 In the mineral exploration chain there are three points where one company is selling the exploitation rights to another company. A piece of land has a certain value, but when there is information about presence of resources, this value will rise tremendously. If this information is incorrect it has huge and costly consequences for the sellers or buyers. This means that this information has to be reliable, and the whole mineral exploration chain must accept the measurement techniques and analysis methods which are used.

3.3 Prospectors and Developers Association of Canada Convention

Now that we understand the basics of the exploration industry, we can analyse the companies which are operating in this industry. To gather data for this analysis I visited last year’s PDAC convention from March 7, to March 10. The Prospectors and Developers Association of Canada (PDAC) represents the interests of the Canadian mineral exploration and development industry. Today, 76 years after its founding, the association is an international organization with 6000 individual members and 950 corporate members.

The association is best known for its annual convention. In 2010, this event attracted over 22.000 attendees from more than 118 countries. At this convention there are 400 exhibitors promoting the latest technologies and products used in the mineral exploration and mining industry. Next to, manufactures of survey tools there are a lot of survey companies.

This was the ideal location to gather data for this research, since both potential customers and Medusa’s competitors were present. The information I gathered by visiting the booths and collecting company leaflets. Besides, I had prepared a list of questions for the different types of companies. Using this list I had semi-structured interviews with the exhibitors. Next to the input from the PDAC, I had a lot of discussions with the involved persons at Medusa. And of course the last important source is the internet, the websites of the manufactures, survey companies and mining/mineral exploration societies.

The combination of this information is outlined in the following paragraphs. First, the potential customers and afterwards the two main competitors.

3.4 Customer description

3.4.1 Tundra airborne surveys

Tundra airborne surveys (TAS) is a company located in Toronto, Ontario Canada. TAS employs four employees, including a senior geophysicist and an experienced survey operator. Because of their small company size, they will only operate on one survey project at the time. TAS mainly offers: precious metal exploration, uranium exploration and geological mapping. These explorations are done with the following techniques: magnetic, radiometric (similar technique as used in MASS) and Very Low Frequency Electromagnetic. TAS own and leases different customized twin prop aircrafts for their surveys.

Airplane type Number Payload

Diamond DA-42 Twin Star 1 500 kg

Piper Navajo 1 1260 kg

King Air A90 Lease 2133 kg

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22 TAS uses a gamma ray detector manufactured by Pico Envirotec, called GRS-10. They own a nine 4.2 litre NaI crystals (8 downward looking crystals and one upward looking). TAS does their data processing with Oasis Montaj and Prage3 (full spectrum analysis).

3.4.2 Precision GeoSurveys Inc.

Precision GeoSurveys Inc. is located in Vancouver, British Columbia Canada. Their work includes doing mineral, diamond, uranium, and oil and gas exploration. In contrast to other exploration companies, they use small helicopters. These smaller helicopters can carry less weight, thus, the measurement tools need to be lightweight as well. Radiometric surveys is their core business, they own a GRS-10 from Pico Envirotec. This is a two 4.2 litre downward NaI crystal. Precision GeoSurveys has five employees. Because their helicopter can only carry limited weight, Medusa’s Lightweight Spectrometer could be very useful for Precision GeoSurveys. The difference in weight between MASS and Pico’s gamma spectrometer is 71kg (100kg – 29kg). This is especially a great advantage when different types of survey systems are combined in one helicopter. (For example, a combination of gamma spectrometry and an electromagnetic survey)

Most survey companies use large crystals, in contrast, Precision GeoSurveys uses smaller crystals. Usually this means less gamma counts and higher uncertainties (less radiation comes on crystal), but because they can fly at a lower altitude, the result are comparable. With this survey technique they deviate from the standards. They probably have to convince their customers of the reliability of this technique. Perhaps they want to take a step further and use the techniques of Medusa, to improve their survey results.

3.4.3 Geotech Ltd.

Geotech Ltd. is a full service airborne geophysical survey contractor, located in Ontario Canada. They use the following techniques: Helicopter-borne time-domain electromagnetic, magnetic, gamma-ray (radiometric). They are specialized in time-domain electromagnetic surveys.

They possess two aircrafts and two helicopters.

Cessna 208B Grand Caravan 2 1877 kg

Eurocopter AS-350 B3 2 1030 kg

Table 3, Airplanes Geotech Ltd. (payloads from flugzeuginfo.net)

Their radiometric measurements are done with a RS-500 system from Radiation Solutions. This is a system with four downward looking crystals and one upward looking. They were pleased to see a much better attended PDAC this year; this could mean a recovery in the mining industry.

3.4.4 Novatem

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23 They notice that the mining industry is recovering from last year’s recession. Since, they sent more quotations. And compared to last year’s PDAC, the on it visitor count increased significantly this year. 3.4.5 Fugro Airborne Surveys

FUnderingstechniek en GROndmechanica (Fugro) is founded in 1962. Fugro started in the Netherlands, but is nowadays grown to a world leading player, with 13.500 employees in more than 50 countries. Fugro activities are carried out across the world, onshore, offshore and from the air, and are primarily aimed at the: oil and gas industry, construction industry, mining sector and governments.

The division from Fugro which is interesting for this research is Fugro Airborne Surveys (FAS). FAS has in total five offices, two in Canada, one in South Africa, one in Brazil and one in Australia. FAS employs 500 employees, most of whom are geophysicists, geologists, remote sensing specialists and field survey operators. FAS offers two types of services, namely, airborne geophysical surveys and interpretation and consulting services. They own 36 different and customized small planes.

CASA 212 3 3920 kg

Cessna 208 Caravan 2 1585 kg

Cessna 210 2 709 kg Cessna 404 1 1618 kg Cessna 406 4 2185 kg Piper Navajo 2 1260 kg de Havilland Dash 7 1 7416 kg Shorts Skyvan 1 2339 kg Commander Shrike 3 960 kg Cresco 750 1 2404 kg

Diamond Twin Star 4 500 kg

Table 4, Airplanes Fugro. (payloads from flugzeuginfo.net)

FAS works for over 40 years with gamma-ray spectrometry. They use the Exploranium GR-820 (predecessor of RSI) or Radiation Solutions RS-500. FAS follows the principles outlined in IAEA Technical Report 323 (Airborne Gamma-Ray Spectrometer Surveying), and in AGSO Record 2000/05 (A Guide to the Technical Specifications for Airborne Gamma-Ray Surveys) for calibration. It is important for FAS that their gamma spectrometers comply with these standards.

Fugro is a ‘big fish’ for the following two reasons. Fugro is the biggest survey company, so if they buy a spectrometer and are satisfied with it, they probably will buy more spectrometer from Medusa. Besides, Fugro is a leading company in the survey industry. If Fugro is using MASS this is the best promotion Medusa can have.

3.4.6 Sander Geophysics

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24

Diamond DA-42 3 500 kg

Cessna 404 1 1618 kg

BN Islander 2 1356 kg

Eurocopter AS-350 B3 1 1030 kg

Table 5, Airplanes Sander Geophysics (payloads from flugzeuginfo.net)

SG also possesses various RSI gamma spectrometer systems. The MASS system could provide a solution for their small lightweight planes. In discussions SG is curious, but critical towards the lightweight approach of MASS. They question the measurement quality of the smaller gamma spectrometers.

3.4.7 SkyTEM

SkyTEM is an airborne service provider based in Denmark. SkyTEM is specialized in helicopter-borne electromagnetic and magnetic surveys and a highly innovative company. The company is merely centred on their in-house developed electromagnetic survey system. These systems are sold world-wide and SkyTEM also provides an air-borne mapping service. SkyTEM does not possess aerial platforms, but their systems are small and relative easy to transport and deploy on rental systems. For example, they lease an Eurocopter B2 or B3 with a payload of 1030 kg. (flugzeuginfo.net, 2010) SkyTEM has shown serious interest in a MASS system. Medusa has provided a demonstration in Denmark and in December 2010, Medusa joined SkyTEM on a paid demonstration project in southern Spain. The SkyTEM team is charmed by the proposition of the MASS system and has requested for a quotation. However, with one of the board of directors affiliated to RSI and the uncertainty of market acceptance of the new technology, this quotation has not led to a sale.

3.4.8 TerraScan

Terrascan is one of the first clients of the MASS system. Terrascan airborne is a service company providing commercial airborne geophysical surveys and is based in Germany. Terrascan airborne provides commercial airborne geophysical surveys on a modern ultra light platform and searches for niche markets in where a ‘green’ approach (low CO2 emission, sensitive natural areas) is favourable. TerraScan has bought a spectrometer from Medusa. The choice of the MASS system for gamma spectrometry helps Terrascan in achieving these goals. Important buying motives for Terrascan were the small and light system, easy to use and friendly software and most of all they wanted Medusa as partner (with knowledge on how to perform and analyse a gamma spectrometric survey) in development and back office.

3.4.9 General

The overview of the survey companies reveals some interesting points. Most employees from the survey companies do not fully understand the techniques used with gamma spectrometry. They use it similar to a thermometer; they want to know the results but are not interested in how it works. They thrust the results from the measurement tools from RSI and Pico.

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25 & gas and mining companies compared to other exchanges. This will also attract other companies in these industries to come to Toronto. Probably, this is an important reason for companies to have their headquarters in Toronto.

There are survey companies which own a gamma spectrometer for over ten years, so the company’s working methods are adjusted to their current spectrometer.

Most exploration companies are small (four until ten employees) this means that they have to buy their gamma spectrometers instead of developing it in-house. They are too small to have the knowledge in-house. This relatively small company size has another consequence. Namely, if they purchase a gamma spectrometer, this is for a small company usually a huge investment. So, a wrong or not usable spectrometer has a huge negative outcome.

Next to the small companies, there are Fugro and Sander Geophysics which are very large. Once there is a successful sale at one of these companies there could be a bowling alley effect. Why the bowling alley effect? “In bowling the key to success is striking the headpin in such a fashion that the combination of the rolling ball and the pins falling into one another causes the maximum number of pins ultimately to fall.” (Wiefels, P., 2002) The more pins the better. Fugro and Sander Geophysics are the headpins in this metaphor, if the headpin is falling there will be probably more sales coming.

3.5 Competitors description

Now that we have collected information from the potential customers, we have to indentify the competitors. They have a large influence on the current performance of MASS. The current performance on an element will decrease if a competitor improves on this same element. Namely, the performance is a comparison of Medusa’s product and the other products in the market.

There are two well-known companies (i.e. Radiation Solutions Inc. and Pico Envirotec Inc.) selling gamma spectrometers, I have spoken delegates from both companies on the PDAC. After a description of the company the specifications of their product will be identified. When this is done for both companies, we can compare these results with the results of Medusa.

3.5.1 Radiation Solutions Inc.

Radiation Solutions Inc. (RSI) is founded by Dr. Jens Hovgaard in 1999. RSI is settled in Toronto. RSI employ approximately 20 employees. They design and manufacture gamma ray spectrometers. They manufacture three different types of spectrometers, namely, airborne, mobile and handheld. These can be used in the following three different industries; nuclear, steel and geophysical. Their spectrometer which is comparable with Medusa’s gamma spectrometer is the RS-500. This spectrometer is sold in two types; the RSX-4 (four downward looking crystal) and the RSX-5 (four downward looking and one upward looking crystal). Relatively weight from the detectors is 91kg and 114 kg.

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26 According to a sales manager from RSI: The market is recovering, but the sales of gamma spectrometers are recovering slower than expected. The sales are not yet on the same level as in 2008 (i.e. before the recession).

Bob Grasty is considered an expert on gamma radiation techniques; he has published a lot of scientific papers. Several of them with Jens Hovgaard (i.e the founder of RSI). Grasty and Hovgaard can be considered as friends, and Grasty will promote RSI and uses the tools from RSI. I spoke with Grasty on PDAC, and there he confirmed the good relation between RSI and himself. Next to that he told, RSI sold thousands of spectrometers around the whole world.

At the moment RSI also sells gamma spectrometers which can be used for (environmental) security. They sold systems which were used during the Olympic Games (2010) in Canada, to detect nuclear explosives.

3.5.2 Pico Envirotec Inc.

Pico Envirotec Inc. (Pico) is also a Canadian company (i.e. Toronto), established in 1992. Pico has around 15 employees. Since 1998 they are primarily manufacture instrumentation for measuring magnetic, gravity and gamma ray radiation data. Mainly used for airborne and ground geophysical surveys for mining and oil and gas.

Pico exists 18 years, and in these years they installed more than 100 airborne systems on aircrafts and helicopters. Clients are mining companies, exploration companies and government agencies. These clients are from around the whole world (i.e. Canada, USA, UK, Austria, Australia, Brazil, China, Czech Republic, Germany, South Africa, India, France, Sweden, Finland, Italy, Egypt, Mexico, Libya, Russia, and Norway).

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4 Constructing an instrument for measuring performance

The following sub question will be answered, in this chapter:

Sub Question 1:

How to construct an instrument for measuring the performance of a supplier of gamma spectrometers?

The goal of this sub question is to construct an instrument for measuring the performance of a supplier of gamma spectrometers. That is, measuring on product performance and on company performance. To be able to measure this we have to find the corresponding performance objectives. There will be four performance objectives related with product performance. And, company performance is formed by three performance objectives. All are shown in Figure 18. All seven performance objectives consist of a number of performance indicators. In the following paragraphs these indicators will be explained and the method of ranking these indicators will also be described.

Product performance Company performance Performance objectives (chapter 4.1) Data analysis software (chapter 4.1.3) Costs (chapter 4.1.4) Response time and dependability (chapter 4.1.5) Logger software (chapter 4.1.2) Gamma spectrometer (chapter 4.1.1) Flexibility of offering (chapter 4.1.6) Reputation of supplier (chapter 4.1.7) Figure 18, Performance objectives

Afterwards (that is in sub question 2), the performance of Medusa and their competitors is measured using this instrument, and this will give a comparison between Medusa and their competitors.

4.1 Performance objectives

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28 performance objectives (i.e. quality, speed, dependability, flexibility and cost) which Slack and Lewis (2008) use in their book. The first three performance objectives quantify the quality of gamma spectrometer, the logger software and analysis software. The fourth is about the costs of the whole system. The last three objectives are about the company, that is, responsiveness, dependability, flexibility and the reputation of the supplier. In the following sections every performance objective and its corresponding indicators is shown in the tables in the paragraph. In these same tables the classifications of these indicators are shown. The classifications determine the score on a performance indicator. The following example on the indicator weight will explain this.

The lighter the system the better. As can be seen in Table 6, a system which weights 100 kg will score a five. And a system with the weight of 20 kg will be scoring a one. Note that, the closest match will determine the score. For example, a system of 35 kg will score a two.

An interesting question is: how are the classification values established. Globally this is done according the following steps.

1. Define the best value in the market, score 1 2. Define the worst value in the market, score 5

3. Calculate the difference between the best value and the worst value 4. Divide the difference by four, and this will be the step size.

For some indicators the steps sizes are not linear. For example, 1000, 100, 10, 5 and 1. This is done to amplify smaller differences. At the indicator number of sold spectrometers the steps sizes are not linear for example. Company A sold zero spectrometers and Company B sold ten spectrometers. (the difference is: ten spectrometers). Company C sold 1000 spectrometers and Company D sold 1010 spectrometers. (the difference again is: ten spectrometers). However, the difference in performance between A and B is much larger than the difference between C and D. This distinction is made by using non- linear indicators, as well.

4.1.1 Gamma spectrometer

The performance objective gamma spectrometer is about the quality of the spectrometer. Slack and Lewis (2008) state that quality often refers to the ‘specifications’ of a product or service. They also state, that another important element of quality is the ‘fit for purpose’. Is the tool capable to do the things it suppose to do? Both statements do apply for the following 11 indicators (shown in Table 7). Gamma spectrometer includes the specifications of the Multi Channel Analyzer (MCA) (i.e. resolution (i1) and max count rate (i2)) and the robustness/ruggedness of the crystals (i4). These specifications of the instrument affect the quality of the output (e.g. detail level and uncertainties). The quality of the output is important for customers, because with output of higher quality, more potential hotspots can be found and with a higher certainty. The indicator compatible with Data Acquisition systems (i3), is the level of compatibility with third party Data Acquisition systems. This is a system which centrally logs the measurement data of diverse tools to a file. The majority of the customers Example: Gamma spectrometer Worse 5 4 3 2 Best 1 i9 Weight 100 kg 80 kg 60 kg 40 kg 20 kg

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29 are using the gamma spectrometer along other measurement tools. They are measuring an area with two or more different measurement techniques (for example, gamma spectrometry and magnetic). This combination is cheaper and gives more reliable results. Therefore the compatibility (i3) could be important.

Crystals are not only looking like glass, but are also very fragile. In a gamma spectrometer the crystal is the most expensive and most important part. This means that the ruggedness and robustness of the crystals (i4) has huge influence on the overall quality of the instrument.

The next indicator is the user-friendliness (i5) of the gamma spectrometer, and means how straightforward is the tool, is it easy to control and understand it? A higher user-friendliness (i5) will increase the productivity. Additionally, it will decrease the chance of making mistakes, because if an operator has to do more and/or complex steps the possibility of making errors in one of these steps increases.

In an airborne survey the gamma spectrometer is mounted in an airplane or helicopter. Many times there is a limited energy supply, in terms of voltage and current. This is the reason of including the indicator power consumption (i6).

It would be an enormous and costly disaster, if after a survey all (or a part) of the survey data is lost. This is meaning that the whole survey must be conduced a second time. To prevent losing data, the gamma spectrometer could features an internal backup (i7) of the measurement data.

Even more advanced is fully autonomous operation (i8). This means that logging can be done without a logging computer, the spectrometer logs the survey data internally. After the survey, the data can be loaded onto the computer for analysis.

Weight (i9) is also a property of the spectrometer, and is largely determined by the type material and the number of the crystals in the detector. A lighter detector creates the opportunity to use it in a smaller airplane. Which is in general cheaper to buy/rent, has lower fuel consumption, and is allowed to fly at a lower altitude. Another innovation could be using a gamma spectrometer in a remote controlled airplane or helicopter.

Next to the weight (i9), the dimensions (i10) of the detector will be strongly defined by the number of crystals in it. For some applications the dimensions (i10 could be an important indicator. The last indicator is the type and quality of the casing (i11). A strong and light casing is important to protect the crystals in the spectrometer. Additionally, the casing is what the customers are seeing, and this will influence the perceived quality of the spectrometer.

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30 4.1.2 Logger software

An important part of a survey system is the logger software. The software will log the measurement data (i.e. write the measurement data to a file) and with this software you can configure the gamma spectrometer. This means that flawless operating logger software is essential when using a spectrometer. The logger software consists of six indicators (shown in Table 8).

The first indicator is robustness of the software (i12), is the software stable, are there any bugs in the software? This is important because bugs can result into incorrect output or unexpected behaviour. Is the software ‘protecting’ users from making mistakes, is another form of software robustness. The second indicator is user-friendliness (i13), and means how straightforward is the software, is the software easy to understand? Next to the indicator robustness, a low score on user-friendliness can also lead to incorrect/unexpected output, because if a user has to do more and/or complex methods the possibility of making errors in one of these steps increases. Additional, a higher user-friendliness will increase the productivity.

The following four indicators are; which features has the software? In other words, does the software support the functionality which the user wants and is expecting? Some features could result

Gamma spectrometer Worse

5 4 3 2 Best 1 i1 Resolution (number of channels) < 256 channels 256 channels 512 channels 768 channels 1024 channels i2 Max count rate from

detector (number of crystals)

1 crystals 2 crystals 3 crystals 4 crystals 5 crystals

i3 Compatible with DAQ (Compatible Open/closed protocol) Not comp. closed Not comp. open Comp. closed Comp. open Comp. open i4 Ruggedness/robustness of crystals (material type) (weaker materials) (weaker materials)

NaI CsI BGO

i5 User-friendliness of hardware Very unfriendly unfriendly Friendly/ unfriendly friendly Very friendly i6 Power consumption (in watts)

90 watt 70 watt 50 watt 30 watt 10 watt

i7 Internal backup Not

supported

External backup

Fully supported i8 Autonomous operation Not

supported Settings cannot be changed fully supported i9 Weight 100 kg 80 kg 60 kg 40 kg 20 kg

i10 Dimensions (in cm³) 80000 cm³ 63750 cm³ 47500 cm³ 31250 cm³ 15000 cm³

i11 Casing/housing Weak,

Heavy, Ugly 2 negatives aspects Neutral 2 positives aspects Strong, Light, Nice