Ayachi Rania

Guillon Delphine

Vareilles Elise

Marmier François

Aldanondo Michel

Coudert Thierry

Geneste Laurent

Knowledge retrieval for configuring risks when answering calls to tenders or direct customer demands

Keywords: Customer/supplier relation, offer elaboration, risk configuration, knowledge based system, knowledge model, case base reasoning

This short article provides the first ideas and results about the configuration of risks when answering tenders or direct customer demands. Indeed, when an offer is defined, it becomes more and more important to analyze possibilities of risks occurrence and their consequences. Most of the time, this analysis is conducted manually thanks to a risk expert. In this paper, we propose to assist the expert with a risk configuration tool that relies on a knowledge base and that allows to define and evaluate: (i) the risk probability, (ii) the main risk impacts and (iii) the interests of various corrective and preventive actions to mitigate it. We first detail the problem. Then we propose a generic model of risks for calls for tenders. Then we describe some knowledge retrieval queries that support the configuration of risk characteristics. As preliminary studies, we will not be able to discuss hard theoretical results but should be able to show a nice a demo of a first software prototype.

INTRODUCTION

This short article deals with offer elaboration when answering call for tenders or direct customer demands. The offer concerns physical product or mechanical systems, called indistinctly in the rest of the paper 'systems'. The customer/supplier relation is assumed to be in a B2B context and in a "light" Engineer To Order situation (ETO) [START_REF] Rivest | Adaptive generic product structure modelling for design reuse in engineer-to-order products[END_REF]. By light ETO we mean that more than 75% of the systems are configured to order (CTO), either Assembly or Make To Order (ATO or MTO); the 25% left are engineer to order (ETO). Globally, such systems are mainly standard but allow some customer specific options that are non-standard, also called ETO options [START_REF] Markworth | Understanding the impact of non-standard customisations in an engineer-to-order context: A case study[END_REF]. These ETO options are a strong point for the supplier's competitiveness.

During the offer elaboration, as there is no guarantee that the customer accepts the offer, we assume that the supplier doesn't study in detail: (i) the design of every ETO option, (ii) their integration with the standard solution and (iii) their production process. The supplier configures in detail the CTO part of the system but just characterizes the key parameters of the ETO 1 Industrial Engineering Center, Toulouse University -IMT Mines Albi, Albi, France 2 Laboratoire de Génie de Production, Toulouse University -INP-ENIT, Tarbes, France 3 ESTIA Recherche -Bidart -France corresponding author e-mail: michel.aldanondo@mines-albi.fr options (among them performance and cost). As a consequence, if the customer accepts the offer, the supplier must design in detail every ETO option, their integration and production process before launching production. This is where the risky point lies as explained by [START_REF] Sylla | Readiness, feasibility and confidence: how to help bidders to better develop and assess their offer's[END_REF]. As the offer has been submitted and accepted with given performance, cost and due date, without a detail study of the ETO options, the supplier takes the risk of not being able to match what he has promised and sold. This means that the final delivered system might be more expensive and/or longer to produce than expected.

We assume that the offer elaboration is achieved thanks to a concurrent system/process configuration [START_REF] Pitiot | Concurrent product configuration and process planning, towards an approach combining interactivity and optimality[END_REF] activity supported by:  a system configuration software in order to configure the CTO part of the system that has some kind of a "design gate" for ETO enabling the user to capture the rough ideas about the solution relevant to ETO options [START_REF] Sylla | Configuration knowledge modeling: How to extend configuration from assemble/make to order towards engineer to order for the bidding process[END_REF], [START_REF] Vareilles | Evaluation and design: A knowledge-based approach[END_REF].

 a delivery process configuration software in order to configure the design activity (for ETO options) and the production activities (for the whole system, from sourcing, assembling up to installing and test) [START_REF] Zhang | Generic Bill of Functions, Materials, and Operations for SAP 2 Configuration[END_REF].

The risk, previously characterized, is therefore attached to the delivery process. Therefore, following the system/process configuration activity, a second activity is concerned with what we call the risk configuration relevant to the delivery process as shown in Fig. 1.

Similarly to knowledge fundamentals relevant to configuration key ideas [START_REF] Felfernig | Knowledge-Based Configuration From Research to Business Cases[END_REF] we consider that it should be possible: (i) to gather risk knowledge and risk processing knowledge in a knowledge base, as a kind of generic model, and (ii) to propose a knowledge interactive process that allows to support risk configuration for a specific risk. In this purpose, the rest of this article goes as follows: in a second section, we identify the knowledge involved in risk configuration. In the third section, we define the risk generic model and the risk configuration problem. In the fourth section, the first ideas relevant to knowledge retrieval queries that can support risk configuration when elaborating offers are proposed.

RISK IDENTIFICATION IN DELIVERY PROCESS

According to [START_REF] Marmier | A risk oriented model to assess strategic decisions in new product development projects[END_REF], risk processing in new product development projects can go as follows. The delivery process is considered as the main input. In our situation, the delivery process gathers a set of tasks as: finalize design, source sub-systems and/or rawmaterials, manufacture, assemble, test and deliver. Each of these tasks is analyzed by a risk expert who identify for each task: (i) the negative event that can be associated to the risk with its occurrence probability [START_REF] Hillson | Assessing risk probability: alternative approaches[END_REF], (ii) the impacts as modifications of the cost or duration of some tasks, (iii) the possible corrective or preventive actions, in order to counter the risk and (iv) the impacts reductions and/or risk probability reductions as a result of these corrective or preventive actions. Our goal is so far to establish a knowledge model and an interactive process to support the person in charge of these identifications that we call risk configuration.

With regard to risks in the customer-supplier relationship domain, most of the works are based on marketing approaches, logistics issues or supplier selection [START_REF] Thun | An empirical analysis of supply chain risk management in the German automotive industry[END_REF] or [START_REF] Hallikas | Riskbased classification of supplier relationships[END_REF]. We retain the work of [START_REF] Hallikas | Riskbased classification of supplier relationships[END_REF] because: (i) they propose a classification of the risks according to the type of customer-supplier relationship, (ii) they clearly differentiate the risks "buyer" and "seller" and (iii) they stress the need to consider the supplier's point of view. Our work is fully in line with this last point. Regarding the risks in offer elaboration, we did not find any work addressing the problem as we formulated it. On the other hand, there is more works and normative elements concerning the risks in project management [START_REF]ISO 31000, International Standards for Business, Risk Management -Principles and Guidelines[END_REF]. We are part of this workflow and especially in the continuity of the approaches proposed in [START_REF] Marmier | A risk oriented model to assess strategic decisions in new product development projects[END_REF] and [START_REF] Fang | A simulation-based risk network model for decision support in project risk management[END_REF], where a notion of risk processing strategy is proposed.

Regarding the modeling and exploitation of risk knowledge to support offer elaboration in customer-supplier relationship, the work is much rarer. Some works exist in civil engineering [START_REF] Yildiz | A knowledge-based risk mapping tool for cost estimation of international construction projects[END_REF] or in information system project [START_REF] Alhawaria | Knowledge-Based Risk Management framework for Information Technology project[END_REF]. As far as we know, only [START_REF] Yildiz | A knowledge-based risk mapping tool for cost estimation of international construction projects[END_REF] proposes knowledge modeling elements for risks. We join in this type of contribution and will propose elements of knowledge models.

As seen previously, the delivery process logically constitutes a first input of risk configuration, because the risks and their impacts and treatments are defined with respect to the tasks of this delivery process. We describe this process as follows:

 The delivery process is associated with a system that is the subject of an offer. A same system can be associated with several delivery processes, in order to compare process variants.

 A process is broken down into tasks linked by precedence constraints. Each task i is performed by a key resource (resource needed to perform it) and is characterized by a cost, ci, and a duration, di, (other metrics could be defined) as shown in Fig. 2.

These data are not sufficient to perform the risk configuration.

Other data relevant to the engineered system or the general context of the offer have to be taken into account by the expert. System characteristics impacting the risk configuration can be for example: the complexity or the size of the system, the maturity of the technologies employed, the reliability of the components used, etc. General context of the offer impacting the risk configuration can be for example: the importance of the customer, the recurrence of the demand, the workload of the supplier, etc.

The risk expert has the knowledge about these characteristics and their impacts on the tasks of the delivery process. They strongly modulate the values of risk probabilities, impacts and impact reductions. We propose to describe these characteristics using the triplet:

(1) Conceptual element, for example: crane system, engine component, offer, customer, etc.

(2) Attribute describing the conceptual elements, e.g. crane complexity, engine maturity, offer recurrence, importance of customer, etc.

(3) Value of the attribute describing the concept, for example, very strong / strong / weak / very weak, high / medium / low. Of course for example : (i) an offer of a high complexity crane with a low maturity engine will be more risky and (ii) risk processing and impact reductions will be stronger if the customer is important.

As a conclusion two inputs will be used by the expert, the delivery process description and the conceptual elements attributes that impacts risk configuration.

RISK CONFIGURATION AND GENERIC MODEL

We consider a risk as a pair (task, event), meaning that the event that occurs during this task correspond with the risk. This is questionable but makes it possible to dissociate the analysis of the consequences of the same event on different tasks. For example, this allows the event "Snowfall and blocked road" to be analyzed differently, depending on whether it occurs during a "Component sourcing" task or during a "Final delivery to customer" task. Remark also that a same task can be the source of several risks. For example, a "Finalizing the design" task can be subject to two risks "Task more difficult than expected" and "Key resource unavailable".

A risk is associated with a set of impacts. An impact is defined for a single risk with:  the impacted task, i.e. the task itself, or some others tasks of the delivery process,  the nature of the impact: cost or duration (or other metrics),

 the method of calculating the impact: either additive (+) or multiplicative (*),  the value of the impact.

For example, the risk " Finalizing the design task more difficult than expected" can have two impacts, one on the "Finalizing design" task by adding two additional days to its duration and the Fig. 2 -Process subject to risk configuration other on the "Assembling and testing" task by multiplying its cost by 1.5. Let's note that a given task can be the object of several impacts resulting from different risks Ri.

A risk is characterized by the probability of occurrence [0, 1] of the associated event, on the studied task [START_REF] Hillson | Assessing risk probability: alternative approaches[END_REF]. This probability can be link to the general context of an offer and some system characteristics. For instance, the probability of occurrence of the risk " Finalizing the design task more difficult than expected" will be higher for a new customer and a very competitive market, rather than for a regular customer with a stable market.

A risk can be mitigated thanks to several preventive and corrective actions. Each corrective or preventive action is a task related to the tasks of the delivery process by precedence constraints. A corrective or preventive action can be associated with different local strategies of the same risk. Each corrective or preventive action is characterized by duration and cost. For example, a preventive action to mitigate the risk "Task more difficult than expected" on the "Finalizing the design" task can be to "train the designers on specific software or design method".

The generic model of a risk is presented in Fig. 3.

In a similar way of product configuration [START_REF] Mittal | Toward a generic model of Configuration Tasks[END_REF], we therefore define Risk Configuration as:

 Given a general context of an offer, some system characteristics and one task of the delivery process,  Given that a generic model of a risk gathers:  Risk configuration consists in (1) characterizing a risk and its impacts on the delivery process, and (2) finding the set of preventive and corrective actions to be added to the delivery process to mitigate the risk.

This configuration activity can be done either by using constraints satisfaction problem or by the exploitation of past cases stored in a database thanks to case-based reasoning (object of this short paper).

For instance, the instantiation of the risk "Task more difficult than expected" on the "Finalizing the design" is presented in Fig. 4.

AIDING RISK CONFIGURATION WITH CASE-BASED REASONING

Based on the principles of reasoning by analogy or case-based reasoning [START_REF] Aamodt | Case-based reasoning: foundational issues, methodological variations, and system approaches[END_REF], our idea is to store in a case base all the information describing the effective realization of past delivery processes (these processes correspond to offers accepted by the customer, the process would not be realized). Then, in the presence of a currently studied offer, the objective is to look for similar items in the case base and retrieve the risk information pertaining for risk configuration in order to provide it as a suggestion to the person in charge of the risk configuration. Three examples of queries relevant to risk, risk impact and risk strategies are proposed.

The first query proposes, for a given task, possible risks with probabilities as follows:  for a given task of a current process offer,  select in the case base, the risk associated to the tasks similar or identical to the given task,  select from the selected risk events, the risk event and its probabilities with conceptual element attributes same or similar to those of the current offer, propose these results to the person in charge.

The second query proposes, for a given risk, possible impacted tasks with impacts values as follows:  for a given pair (task, event) of a current process offer,  select in the case base, the impacted tasks affected by a same or similar pair (task, event),  select from the selected impacted tasks, the impacted tasks and their impacts values which are the same or similar to those of the current offer, propose these results to the person in charge.

The third query proposes, for a given risk, possible strategies with corrective/preventive actions as follows:  for a given pair (task, event) of a current process offer,  select in the case base, the impacted tasks affected by a same or similar pair (task, event), in a similar way as for the second query,  select in the case base, the risk strategies with their corrective/preventive actions which are the same or similar to previously founded impacted tasks,

Fig. 1 -

 1 Fig. 1 -Offer elaboration and risk configuration



  i. a set of events, ii. a set of possible impacts, iii. a set of impacted tasks, iv. a probability of occurrence, v. a set of preventive actions, vi. a set of corrective actions, Given a set of constraints linking general context, system characteristics and risk model items,

Fig. 3 -Fig. 4 -

 34 Fig. 3 -Risk Generic Model

ACKNOWLEDGMENTS

The authors would like to thank all ANR OPERA partners and the French ANR agency for work funding.

 select from selected risk strategies, corrective/ preventive actions with conceptual element attributes same or similar to those of the current offer, propose these results to the person in charge.

These three queries are given as examples. Other one can be established. They provide a strong support to the person in charge of risk configuration in the sense that they avoid him to rely only on his own knowledge or risk expertise.

CONCLUSION

The goal of this short article was to provide first elements in order to set-up to a knowledge-based support system for risk configuration when answering tenders or direct customer demands. Risk configuration knowledge has been identified, a generic model of risk was provided as well as a risk configuration definition. Some examples of queries to assist risk configuration by the use of past cases have been also provided.

Two main interests of this proposition are:  to support and to give confidence to the risk expert suggestions,  to allow being less human expert dependent. In a more operational and industrial level, another key interest of this proposition is to allow companies:

 to reduce the level of expertise required to engineer conventional risks (with a junior risk expert for example)  to leave more time to senior experts to focus on unconventional risks (new risks or critical risks, for example).

Given all these elements and according to the approach advocated in [START_REF] Marmier | A risk oriented model to assess strategic decisions in new product development projects[END_REF] that proposes to use a discrete event simulator, the expert is now able to:  configure the risks of a given delivery process taking into account the offer context and system characteristics,  simulate the delivery process with all possible combinations of risk occurrences taking into account corrective and preventive actions  and evaluate for each combination of risks, the relevant metrics and probability of occurrence.

These simulations allow the expert to evaluate all the scenarios from the worst one (with all the risk occurrences and no relevant preventive and/or corrective actions) to the best one (no risk occurrence and no additive expenses or loses of time due to preventive or corrective actions), and to give for each of them the probability of occurrence and the value for the relevant metrics (cost and duration). Therefore, in this study, this first level of risk configuration/simulation allows the expert to know "what could happen if things don't go as they should with and without preventive and corrective actions".

As far as we know, we did not find any scientific work relevant to this problem. We are at the present time beginning to prototype and test this knowledge base system with four companies from industrial and service sectors. The next issue is to add some rulebased decision aiding, assuming that some generic risk configuration rules can be extracted from the case base.


Keywords: Automobile grinding residues, metallic materials, stabilisation, beneficial reuse

INTRODUCTION.

For decades some 75 per cent by weight of an End-of Life-Vehicle (ELV) have been recycled, and currently go mainly to landfill sites. This portion of the vehicle is made up more or less equally of inorganic and organic substances. The organic substances are mainly plastic materials followed by a small quantity of modified natural substances such as cellulose fiber products or leather. Metallic materials from ELVs are relatively easy to recycle without major input of costly manual labour. The separation of ferromagnetic materials from other metallic materials is also easy and relatively inexpensive.

Since the techniques for recycling metals are targeted specifically at their material properties, metals can only be recycled as metallic materials although it is often necessary to subsequently produce other alloys from these metals to enable their use in alternative product applications. However, recycling of automobile using grinding process generates also fines particles which contains plastic and metallic materials like Chromium, lead, iron, copper and zinc among which some are toxic at low concentration. There are not many process available for the treatment of these contamined fines particles which is landfilled at this time. We are developed adequate processing methods to transform metal ion from automobile grinding residues fines particles (AGRFP) into new products for beneficial reuse using phosphates. Minerals can be recycled if they are non-hazardous. Heavy metal stabilisation, i.e. converting trace metal ions into insoluble, stable and non-leachable compounds is a key step for our process. We feel the issue goes beyond incorporating the minerals in a properly selected matrix and is well worth considering specific treatment methods in order to obtain desired properties.

The process use is based on stabilisation of heavy metal using phosphates. In fact, Solvay have recently developed a new treatment uses phosphoric acid to neutralise fly ash basicity and form insoluble metal phosphates. It is composed of four parts: fly ash is washed and filtered to extract soluble salts (mostly chlorides) before chemical treatment with phosphoric acid. Thermal treatment transforms the solid into a stable mineral phase. In order to engineer the final product to have the desired properties for end use, we studied the control of the physico-chemical properties by specific thermal treatments. This example was applied in REVASOL experimental project leading to the reuse of stabilised fly ash in road construction.

The calcination of the chemically treated waste gives solid residues containing apatite mineral-like insoluble metal phosphates without generating volatile metal chlorides and oxides. Calcination significantly affects the solubility of the metals ions. The treatment under mild conditions contributes to apatite crystallisation. Such transformed material with stabilised trace metal ions may be considered for beneficial reuse. In fact, These apatite containing solids are stable residues which may be added to various materials to facilitate recycling and beneficial use in highway, concrete or cement products.

Eliminating disposal sites and transforming hazardous materials into new products for beneficial reuse is an investment for a better future. Sustainable growth in the automobile recycling area will only be possible with recycling of the AGRFP.

The paper will focused on the review of the literature concerning the treatment of AGR and on an example showing how chemical treatment with phosphates and thermal treatment (calcination) can modify several solid waste containing heavy metals and transform its components into environmentally friendly products or natural resources conservation products. In this paper, the incineration fly ash will be taken as an example of valorisation of solid waste containing heavy metals.

1

BECOMING OF AN ELV.

Automobile Waste: « zero tip » [1].

Every year, in France, 1.8 million of End-of-Life Vehicles (ELVs) go for scrap. These wrecks, that weigh a ton on average each, are recycled to 75% (essentially metals), which places the car among the more recycled products of current utilisation. The 25% Ideally, a leading recycling center, where all activities are regrouped in only one site, is able to reprocess until 95% of the car weight.

The pilot recycling centers process about 220 000 ELVs per year. They allow the recuperation of metals, glasses, tires, liquids, and of some plastic materials. Residues are largely used as combustible in cement factory. Technically, all operates, stay only one obstacle to the generalisation of such pilot centers: the absence of real industrial paths to use the recuperated materials and to make of the recycling a profitable business.

The agreement, signed in 1993 by constructors, the authorities and actors of the recycling, that set themselves the target to recycle 85% of the car weight in 2002, and 95% toward 2015, specify indeed that "these objectives will only be achieved if this path finds by itself its economic balance". Excepted these two pilot centers, the majority of cars is processed by the traditional way. Breakers disassemble what is most profitable to resell: aluminium, copper and mechanical pieces. Most serious among them, a minority, clean up the cars. For lack of industrial paths to recycle other materials, they are content with recovering the ferrous and non-ferrous metals (that represent more than 70% of the car weight all the same), the remainder going to the tip.

• Cleaning up

This operation consists in emptying the car of all its liquids (oil, liquids of windscreen, cooling and brakes) and to remove the battery. Tires are also disassembled. This first step is indispensable. Indeed, a car non-cleaned up will corrupt the quality of the AGRs destined to the tip. These residues, in this state, will be therefore a supplementary pollution source. Oil is recycled or used as combustible in cement factory. The usable tires are retrodden, others are ground to serve combustible in cement factory. Plastic (polypropylen) and the lead of batteries are reused as raw materials.

• Disassembly

The glass is recuperated. For plastic, the disassembly limits itself for the meantime to polyurethane mosses of seat and polypropylenes, mainly present in shields. Some nonferrous metals, as the aluminium or the copper, are recuperated also. The catalytic exhaust pipes are disassembled in the goal to collect the rare metals that they contain (platinum and rhodium). Some mechanical pieces, as motors, are got back before being renovated and sold second-hand. After treatment, the glass is transformed in fiberglass, bottles or food packings. Mosses of seats are recycled in soundproofing and insulating.

And shields are useful to manufacture new shields. Non-ferrous metals are melted and reused as raw materials.

• Sorting Wires of copper, previously disassembled, are stripped in a separated workshop. It's a manual operation, justified by the price of this raw material.

• Grinding

The grinder tears carcasses of cars to shreds. Begin the different steps of the automatic sorting then: a magnetic pulley separates the ferrous metals destined to be remolded; a system of blowers separates the slight wastes (mosses and shreds of plastic) good for the tip; an electric current separates non-ferrous metals of the thickest pieces of plastic; a bed of water finally separates non-ferrous metals the some of others, the heavy (zinc, lead, copper) remaining under water and slightest (aluminium, magnesium) coming back up to the surface. Grinding residues are to their turn sorted out in two parts: the organic residues (plastic, rubber) usable as combustible in ovens of cement factory, and the mineral, incombustible residues, that leave to the tip.

Between 90 and 95% of the weight of a car has been recycled, against 75% in a classic treatment limiting itself to the recuperation of metals. In the assumption of a reuse of the mineral grinding residues, to do embankments for example, 100% will even be reached. Cars will be then completely recyclable.

VALORISATION PROCESSES OF ELVS.

Incineration of wastes.

According to their origins, the incinerated wastes bring energy, according to their Lower Calorific Value (LCV), interesting physical elements for the manufacturing of the cement (wastes of iron oxide of the metallurgy, silica of foundry sands, alumina...).

The heavy metal rejection generates an important problem however most of heavy metals are toxic and are not destroyed during the combustion process. They undergo in fact simple chemical transformations.

Valerco and Vicat: Residues are used as combustible.

The automobile grinding site at Saint-Pierre-de-Chandieu in France, prefigure the complete path of the automobile recycling. Several units of the "French Company of scrap metals" (CFF) are established there: the grinding Purfer, the demolition worker Ecoval, specialist of the cleaning up and the disassembly, created in partnership with PSA.

In fact Valerco is the results of a partnership between the CFF and the Vicat cement factory, valorise about 15 000 tons of AGRs per year. Created in 1991, the Valerco society has for mission to prepare the combustible stem from grinding residues (provide by the grinding Purfer). This combustible is destined to be burnt in ovens of the Vicat cement factory, installed at Montallieu, in Isère (France). On the 30 000 tons of AGRs that Saint-Pierre-de-Chandieu generates every year, only half enters in the composition of the combustible.

Indeed, after a first sifting of residues, close to 15 000 tons appear under form of "fine", mainly organised by minerals (silica, calcium salt, oxide of iron). These wastes are destined to the tip. Remain 15 000 valorisable tons organised of moss, rubber and various plastics. It is on this material that Valerco operates, pulling to pieces it with the help of a grinder with knife to form tablets of fissile material of a 6 cm maximum diameter. A new technique for product preparation allowed a significant lowering of their chlorine rate; the faculty to the burning thus improved allows to offer other openings.

To burn the AGRs, the Vicat cement factory installed a system of precalcination, allowing to destroy all components of the AGRs, including heaviest. "We are today to consider the AGRs like a classical combustible", confirm Raoul de Parisot, Director of the cement branch at Vicat. Thanks to the incineration of the AGRs, the site of Saint-Pierre-de-Chandieu valorises End-of-Life Vehicles to height of 87%.

Cement industry and the stabilisation of wastes [3].

In the same way, the Research and Development department of the Vicat group developed new cements for concretes with high resistance. Vicat developed in 2001 a binding of stabilisation (LIV) to reply the requests of the market of waste stabilisation (stabilisation of the municipal solid waste incineration fly ash).

The thermolyse process.

The incineration consists in eliminating waste by burning it (temperature superior to 850°C) with air atmosphere, while the thermolyse consists in decomposing waste by heating in poor air atmosphere at temperatures from 450 to 750°C.

The thermolyse certainly has a place to take among techniques of waste treatment.

The thermolyse does not constitute a total treatment of wastes, but a partial treatment that emerges on a solid-fuel. The thermolyse must be designed therefore upstream of an existing industrial unit able to use this combustible.

The residue of thermolyse is a carboned residue that is under the form of a homogeneous black coal powder, constituted of elements of a few millimeters. Its calorific value evidently depends on the incoming wastes. The residue stem from standard domestic wastes has a calorific value of 18/20 MJ/kg, that situates it in the poor ashy coal category.

This combustible presents advantages that it is a combustible of renewable substitution endlessly, with a significant calorific value, and with possibilities of consumption spread out in the time, since it can be stocked before a future utilisation, correlating to a peak of consumption.

The solid-fuel can be interesting for high energy consumer industries by increasing the rates of substitution of their combustible. Utilisations in metallurgy and in power station are in progress. However utilisations in cement factory constitute the best way today.

The important fact is to recall that the utilisation in cement factory would suppress all ultimate solid residues while incorporating the mineral materials contained in coke in components of the cement. The washing of the solid stem from thermolyse allows to eliminate an important fraction of chlorine, inerts and metals.

The implantation of a thermolyse unit should be situated ideally close to a fossil energy user (valorisation of the thermolyse gases). The thermolyse solid-fuel is used ideally as combustible of substitution in cement factory.

Temperatures of treatment being weak, and the thermolyse being realised without oxygen, the heavy metals are not oxidised, nor volatilised (to the exception of mercury, and of cadmium whose emissions are lower to norms), what facilitates their recuperation and their elimination.

Thermolyse only generates very little pollution. First of all, since there is not combustion of wastes, but only combustion of gas, the volume of smokes is reduced (decreases of about 50% with regard to the incineration). But, especially, the system allows a perfect chlorine neutralisation by washing the carboned solid.

The ferrous and non-ferrous metals in output of thermolyse have an incomparable quality with the one of metals in output of incineration (it is not mixed to wastes), and even better than the one of metals recuperated in center of sorting, as they are ridded of all complementary element (plastic, painting, water...). The price of trade-in should be elevated therefore. It is only about potential revenue that depends on the recuperation (magnetic current, current of Foucault...). It is able therefore to be interesting to mix treated wastes with the DIBS in order to increase valorisable fraction and to justify a complementary sorting plant.

TREATMENT OF INCINERATOR FLY ASH WITH PHOSPHORIC ACID AND

VALORISATION [4, 5, 6, 7, 8].

The fly ash particle size distribution (mean size), determined with a Mastersizer laser granulometer (Malvern), is 24 µm. Fly ash density of 2.75 g.cm -3 was obtained with a Micromeritics 1330 gas pycnometer.

X-fluorescence measurements were made with a Philips SEM with energy dispersive analysis for major elements (calculated in oxide form) and ICP (Inductively Coupled Plasma) for minor elements. The weight percent of species found is : Al 2 O 3 (9 %), CaO (25 %), Fe 2 O 3 (8 %), SiO 2 (18 %), SO 4 (20 %), Cr (1126 mg/kg), Cu (2552 mg/kg), Pb (12500 mg/kg) and Zn (28500 mg/kg).

The structure and the composition (Ca/P molar ratio) of the dried powders was identified and quantified by X-ray powder diffractometry (Siemens D5000). XRD measurements were carried out with CuK α radiation. The phases present were determined by comparing the patterns with JCPDS standards.

The specific area of the ground powders were determined by nitrogen adsorption using a BET method (MICROMERETICS Gemini Vacprep 061).

The shrinkage of powder was followed by dilatometry (SETARAM Setsys16/20) with 5 g constant load on the sample. In parallel, calcination experiments were carried out on a furnace of two liter volume equipped with mass loss measurement. We have shown that calcination of the chemically treated waste gives solid residues containing apatite-like insoluble metal phosphates and help to significantly modified properties of final residues like specific surface area and density [5]. Such transformed material with stabilized trace metal ions may be considered for beneficial reuse.

Modern society is willing to pay to get rid of household refuse. Collecting, sorting and landfilling has a low cost but does take care of the immediate environmental impact of municipal solid waste. Incineration has an increased cost but contributes further to reduction in volumes and also allows for some generation of heat or energy. Further treatment of bottom ash, fly ash or air pollution control waste means another additional cost. The return is the possibility of recycling completely the initial waste. Eliminating disposal sites and transforming hazardous materials into new products for beneficial reuse is an investment for a better future. Sustainable growth in the incineration industry will only be possible with recycling of the minerals in the fly ash in civil engineering.

An example of really valorisation by this way is the road construction near Dombaslesur-Meurthe (France), where the phosphored-calcined fly ash were used as material in the road. This example will be developped during the Congress at Geneva.

TREATMENT OF AGRS WITH PHOSPHORIC ACID AND FUTURE DEVELOPMENT.

Characterisation of AGRs.

The AGRs are characterised by organic materials content of about 20%; the weight loss at fire to 900°C is 24% (23% to 600°C).

The element analysis is made using atomic absorption and the results are presented in The results show that the concentration of heavy metals in AGRs is more significant than those of fly ash. This fact explain the reason why AGRs must be treated before reused or landfilled.

Results of Phosphatation of the AGRs.

Combined mud-AGRs stabilisation.

These experiments aim to the stabilisation of mixture of port mud and Automobile Grinding Residues.

Mud is characterised by a relatively important content in calcite (25 (w)%); the content in dry material is weak (32 (w)%), this dry material containing about 6 (w)% of NaCl.

The content in organic materials is near to 13 (w)%; the sulphides is relatively show (0.68% S). Tests of stabilisation (without solidification) have been realised at three different temperatures: 625, 750 and 875°C, and by using a concentration of phosphoric acid of 7.5 and 10 (w)% against the raw dried product.

Chemical analysis

The phosphatation have a very important effect on the leachability of the Cr, Zn and Pb heavy metals. However, for the lead, the first leachate using French X31-210 standard are not satisfying, in fact the concentrations of this metal always being over 1 mg/l. The rise of the calcination temperature is a positive factor on results.

The solidification of the "phosphated-calcined" AGRs should products satisfying materials to the leaching test; nevertheless it would require a previous thin grinding of these products, which is expansive. This fact is at the origin of the choice to achieve tests of combined "mud-AGR" stabilisation-solidification, by limiting the ratio of AGRs so that the thin component, i.e. the mud, is clearly majority.

Results of the combined Mud-AGR stabilisation, without fragmentation of the

AGRs.

The phosphatation has been achieved separately:

-for the mud (2.5 (w)% H 3 PO 4 in relation to the dry);

-for the AGR (10 (w)% H 3 PO 4 ).

Phosphated products were:

-calcined separately, and mixed;

-or mixed and calcined.

The ponderated ratio mud (dry) / AGR has been fixed to 3 / 1.

The calcination has been achieved in the usual conditions at 625 and 875°C (start cold oven, a plateau of 2 hours at the temperature).

The effective stabilisation of heavy metals is incontestable, according to the leaching test and mechanical properties.

It appears that the practice of the phosphated products mixture before the calcination does not present any inconvenience, what is evidently simpler at the industrial scale.

Results of stabilisation and solidification of Mud-AGRs mixtures.

The calcined products have been solidified with the cement of blast furnace then, in ponderated ratio 9 / 1 (manual mixture with the cement, without attrition).

The preparation of mortars requires an important quantity of water (between 35 and 40g of water for 100g of dry) that is not on the favour of good mechanical properties.

Effectively, for all samples, the resistance to the compression after 28 days reveals to be mediocre, and on average below 2N/mm 2 , limit value for a solid waste (French norms).

The observation of solidified sample sections shows:

-the very important irregularity of surfaces, due to metallic particles (Fe) that break away at the time of the cutting;

-the porosity of solidified products.

Figure 1 :Figure 2 :

 12 Figure 1: Evolution of the specific surface area function of temperature.

Table 1 :

 1

	Domestic wastes	Tires	AGRs	Plastic	Muds

Balance material and LCV (LCV of 1 kg of coal = 30 MJ/kg, LCV of 1 kg of fuel-oil = 38 MJ/kg) according to wastes treaties in thermolyse (Source: Free University of Brussels).

Table 2 .

 2

	Chemical analysis	Cd	Cr	Cu	Fe	Ni	Pb	Zn
	(mg/kg)	64	210	2800	120000	600	11200	17400

Table 2 :

 2 Chemical analysis of AGRs.

	Otherwise, by simple acidimetry, the carbonate of calcium (CaCO 3 ) content can be
	estimated to 3.1 (w)%.
	Tables 3-6 detail the characterisation of the four analysed AGRs.

Table 3 :

 3 Origin of samples of analysed AGRs.

	Chemical analysis (g/kg)	C	H	O	N	S	P
	AGR-0	112.00	15.40	103.90	5.30	15.30	--
	AGR-1	348.27	49.47	151.10	5.00	traces	80.80
	AGR-2	242.63	27.97	142.80	3.10	traces	32.40
	AGR-3	204.40	23.00	95.40	4.80	0.90	34.80
	Chemical analysis (mg/kg)	Cd	Cr	Fe		Pb	Zn
	AGR-0	45	644	161814		9185	21054
	AGR-1	33	73	105640		1224	7533
	AGR-2	42	42	71580		1168	2439
	AGR-3	15	187	70120		1728	18719

Table 4 :

 4 Chemical analysis of AGRs, Composition in heavy metals.

		AGR-0	AGR-1	AGR-2	AGR-3
	Density (g/cm 3 )	2.5214	1.642	1.772	2.135
	For diameter < 1 mm		2.072	2.176	2.244

Table 5 :

 5 Density and Specific Surface Area of analysed AGRs.

		AGR-0
	LCV (kJ/kg)	4516

Table 6 :

 6 LCV of analysed AGRs.

Table 7 :

 7 Chemical analysis of Mud.

		Cd	Cr	Cu	Ni	Pb	Zn
	(mg/kg)	11	33	37	8	160	2520
	The process of stabilisation (2.5 (w)% H 3 PO 4 , 625°C) -solidification gives very
	satisfactory results of the point of view of:
	-the mechanical resistance (superior to 10 N / mm	2 );
	-the behaviour during the leaching tests.
	4.2.2 Combined stabilisation Mud-AGR without fragmentation of the AGRs.
	The AGRs are characterised by organic materials content of about 20 (w)%; the weight
	loss at fire to 900°C is 24 (w)% (23 (w)% to 600°C).
	Chemical analysis	Cd	Cr	Cu	Fe	Ni	Pb	Zn
	(mg/kg)	64	210	2800	120000	600	11200	17400

Table 8 :

 8 Chemical analysis of AGRs.

CONCLUSION.

The results obtained both with incinerator fly ash and automobile grinding residues (AGRs) show that the calcination of the chemically treated waste gives solid residues containing apatite-like insoluble metal phosphates and help significantly modified the properties of final residues like specific surface, density, hardness and leachability of pollutants.

The REVASOL which is a demonstration project developed by SOLVAY lead to re-use the stabilised in road construction. For this reason, the stabilisation of heavy metals with phosphoric acid from AGRs would represents a promising way to re-use these residues.

REFERENCE :

1 Cahiers Industries, Le Recyclage Automobile, Industries, N°23, Décembre-Janvier 1997. 6 Eighmy TT., Crannell BS., Cartledge FK., Emery EF., Oblas D., Krzanowski JE., Shaw EL., Francis CA., Heavy metal stabilization in municipal solid waste combustion dry scrubber residues using soluble phosphate. Environ. Sci. Technol. 1997, 31:3330. 7 Nzihou A., Sharrock P., Calcium phosphate stabilization of fly ash with chloride extraction. Waste Management, 2002, 22:235. 8 Derie R., A new way to stabilize fly ash from municipal incinerators. Waste Management, 1996, 16(8):711.


Saïna Hassanzadeh

Didier Gourc

François Marmier

Sophie Bougaret

Decision-making under uncertainty in drug development

In pharmaceutical industry, decision-makers have to decide whether to continue drug development projects, if the tests results on new compounds are good enough. Such decisions are made collectively, under a high degree of uncertainty and in non-emergency situations. These projects are very expensive, risky, and long. The major problem in this context is indecision. In order to improve the decision-making process in practice, we need to characterize and analyze situations of decisionmaking under uncertainty. In this paper, we propose a new defi nition of uncertainty that takes human factors in its characterization into account. Then, the factors that contribute to generate, characterize, perceive or process uncertainty are structured in a typology. That helps us recognize and explore causal and infl uential factors of uncertainty. Additionally, based on interview results, we present a description of the decision-making process in pharmaceutical R&D, illustrating the role of different actors, their interactions, and the fl ow of information. This should help decisionmakers adopt proactive practices instead of reactive ones.

Introduction

Decision-making in R&D faces much uncertainty in all industries. The development of new products implies dealing with uncertainty that comes from innovation in product development process, market dynamics, and changes in regulation. Many questions need to be answered in order to make decisions during the development project. In pharmaceutical industry, the degree of uncertainty is particularly high, since even if many tests are performed on animals, the behavior of the new compound in human body cannot be known.

A drug development project is defi ned as a process that allows a presumably active chemical or biological entity to become a pharmaceutical drug. After passing a series of tests, the drug is certifi ed for commercialization, guaranteeing its safety, effi cacy, and quality [START_REF] Gourc | L'industrie pharmaceutique : ses projets de développement, leurs caractéristiques et leur management, La cible[END_REF]. Drug development projects are composed of different phases, separated by Go / No Go decision milestones, wherein a steering committee decides whether to continue or stop the project. These decisions are based on project status information and the results of the studies which are generally very poor compared to what is required to make an informed decision in optimal conditions. Drug development projects last an average of 13.5 years and cost about $ 873 million, with a success rate of only 4% (Paul et al. 2010). The cause of this high attrition rate is not related to the lack of management of time, costs, and resources. Planning is a crucial, diffi cult, and necessary task for project success but it is not suffi cient. There are unclear zones that we are not able to recognize at an early phase of a project (Perminova et al. 2008). In drug development, the main reason of this high attrition rate is the lack of knowledge about the safety, effi cacy, and quality of the molecule during the fi rst phases of the project. In a full 50% of lately stopped projects, failure is due to lack of effi cacy, 30% to lack of safety and 20% are not safer nor more effective than the drugs already available on the market [START_REF] Gordian | Why Products Fail in Phase III? IN VIVO[END_REF].

In this context, decision-making process is characterized by: 1) a strong degree of uncertainty: when the profi ts and risks are unknown, as it is usually the case in drug development projects, the degree of uncertainty is high and the choice is diffi cult, 2) non-emergency situations: in R&D, decisions to be made do not seem urgent, comparing accident, crisis, and disaster contexts, but a potential danger could arise in the future. Previous research works concentrate on risk and uncertainty in emergency situations, but for the fi rst time, to the best of our knowledge, ours considers nonemergency situations, wherein it is quite possible to postpone the decision, waiting for complete and accurate information. Situations in which decisions may appear without urgency include the choice of investments, renewal and modernization of equipment, and the introduction of new safety devices, 3) the collective aspect: individual differences within a group play a crucial role in interactions between experts and could complicate the decision or indecision processes and engender or increase uncertainty.

The structure of the paper is as follows. First, we review two major approaches to defi ne and identify uncertainty: the objective approach and the subjective approach. We present our defi nition, which includes both subjective and objective aspects contributing to uncertainty identifi cation. Next, we present a typology of uncertainty factors related to the subject, object and context. Then, we review how decision-making process is defi ned in the literature and present our description of decision-making process in drug development. Our description is illustrated by a case study based on a real application.

State of the Art

Defi ning and identifying uncertainty The most fundamental capability of human beings is conscious decision-making. In order to better understand decision-making process, we need to understand the notion of uncertainty fi rst (Klir 2005). Economists are interested in defi ning uncertainty in order to identify and control it. In economics, uncertainty is defi ned either based upon the impossibility of calculating probabilities as in the Knight's defi nition, wherein uncertainty is defi ned as a situation in which it is not possible to specify numerical probabilities (Knight 1921), or by emphasizing the lack of information in a more general sense [START_REF] Galbraith | Designing complex organizations[END_REF]Thiry 2002;Klir 2005).

Psychologists and sociologists defi ne uncertainty either through a state of mind characterized by "doubt, or a conscious lack of knowledge about the outcome of an event" (Head 1967), or through its consequences: "uncertainty is the inability to act deterministically" (Thompson 1967), "uncertainty is a sense of doubt that blocks or delays action" (Lipshitz & Strauss 1997). In psychology, "in the contrast to the decision theory approach, psychological uncertainty is not a part of the external environment, such uncertainty may be a mental reaction to the external environment, but it is a psychological phenomenon existing only within the mind of the person who doubts" (Head 1967).

In economics, uncertainty is characterized by the lack of information about events and human factors are not taken into account. Thus, in this context, uncertainty is objective and exists independently of the existence of an uncertain subject. In contrast, in psychology, the emphasis is on human's mental state and uncertainty is relative to a subject.

Similar to scholarly defi nitions of uncertainty, dictionaries often defi ne uncertainty either by emphasizing the object or the subject. For example, the Cambridge dictionary defi nes uncertainty by emphasizing the object: "when something is not known", whereas Webster focuses on the subject: "the state of being unsure of something". Objective and subjective approaches are also identifi able in philosophers' literature. Aristotle, Descartes and Laplace only admit logic and mathematical rules to construct certainty. Socrates, Plato, Carneades, Pascal and Kant accept other ways of certainty construction such as faith and emotion.

When a subject is uncertain about an object, where does the uncertainty come from? Is it in the subject's mind or does it come from the unpredictability of the object's comportment? We think it is important to take human factors into account in the characterization of uncertainty. In our defi nition, uncertainty is a subject's conscious lack of knowledge about an object which is not yet clearly defi ned, in a context requiring a decision. Uncertainty cannot be defi ned neither as only pertaining to the subject nor to the object, because a subject could be uncertain about an object, while another subject is certain about it. Hence, uncertainty is a relationship between subject and object.

Furthermore, context is an important factor in defi ning uncertainty. A subject could be uncertain about an object but if he does not need to make a decision nor perform an action, this situation is not considered to be an uncertain situation. For example, I am not sure whether the laboratory building is accessible during the weekend or is closed due to construction, but since I do not plan to go there this weekend, this situation does not concern me. This defi nition of uncertainty includes the three elements that contribute to the identifi cation of uncertainty: subject, object, and context.

Typology of uncertainty factors

Figure 1 outlines the main categories of the factors that contribute to generate, characterize, perceive or process uncertainty. This typology is based on three axes of the uncertainty defi nition: subject, object, and context: 1) factors of uncertainty related to the subject are divided into two sub groups: the subject's psychological traits and his professional experiences as individual factors and contradictory opinions and debates as collective factors, 2) factors of uncertainty related to the object refer to two sub groups: the states of the object that are dynamic and the goals of the subject that depend on the object's states, 3) factors of uncertainty related to the context also refer to two sub groups: internal factors such as the organizational and hierarchical factors which do not favor the circulation of information inside a company and could increase the level of uncertainty. Likewise, external factors exist such as market dynamics, competitors' activities, stakeholders' expectations, regulatory changes, and doctors' conviction in a new drug, which make the environment of decision uncertain.

The comprehensive vision of this typology helps us understand the sources and the infl uential factors of uncertainty associated with the manager and the project team (subject), with the project (object), and the environment (context) of the decision. This allows us to control some of the uncertainty sources in order to reduce it as much as possible and deal with what remains according to the type of the source. Simon has suggested that "a decision is not an act, but a process" (Tsoukiàs 2008). The process involves selecting the best among several options through a proper evaluation of the parameters of each option and its consequences (Panneerselvam 2006). However, "all decision is a matter of compromise. The alternative that is fi nally selected never permits a complete or perfect achievement of objectives, but is merely the best solution that is available under the circumstances" (Simon 1947). Generally, decision is the result of interactions between preferences of individuals.

The decision process mainly consists in these interactions, under the various compensating and amplifying effects of the system that make up what we shall call the decision process (Roy 1996).

The decision-maker usually chooses an opt ion based on t he balance of benefi t / risk of available options. If he knows all the possible options and their consequences, he is in the case of a deterministic decision. For example, in maintenance management, if the annual maintenance cost and the annual operating cost of equipment are known in advance and are not subject to any change in the future, then the decision about the economic life of the equipment is a deterministic decision (Panneerselvam 2006). In the case of non-deterministic or decision under uncertainty, information about different choices and their consequences is partial for the decision-maker. The degree of uncertainty could be different. This difference corresponds to the difference between required information and available information.

A decision-making iterative process in four stages has been proposed by Simon: Intelligence stage as the fi rst stage comprises information collecting and problem identifying, Design stage centers on an alternative analysis and construction (invent, develop, and analyze), Choice stage focuses on alternatives evaluation, and Review stage consists of evaluating earlier decisions and satisfaction level (Simon 1977). Janis and Mann propose a vigilant decision-making process which takes into account any new information or expert judgment to support the choice process (Janis & Mann 1977). Based on these two processes, in the next section, we propose a global vision of decision-making under uncertainty in drug development projects. The objective is highlighting the role of different actors and the fl ow of information.

Decision-making process in pharmaceutical R&D

Global vision

Figure 2 represents two dimensions in decision-making process: the actors with their positions in a pyramid form and the fl ow of information in italic font. We distinguish four macro-stages in the decision-making process: 1) Intelligence and Design stage, 2) Test stage, 3) New Information Analysis stage, and 4) Choice and Review stage. The fi rst stage, which corresponds to Simon's model (Simon 1977), includes problem identifi cation, information collection, and solutions development. The steering committee needs information about molecule activity and behavior in human body, in order to decide whether or not to continue the project. Project goals and a list of questions about the characteristics of the molecule are transmitted to the project team in charge of defi ning the Target Product Prof ile (TPP) as a key st rat egic t ool, which guides drug development. TPP is the key design template for creating the development plan and should be defi ned by the project team as it is a multidisciplinary task (Kennedy 1998). Focusing on the TPP, the project team determines a list of tests and operational conditions for technicians.

The second stage corresponds to the fourth stage of Janis and Mann's model: searching new information relevant to the choice. In this stage, the technicians carry out the tests and provide the raw data (Janis & Mann 1977). The third stage corresponds to the fi fth and sixth stages of Janis and Mann's model: "taking account of any new information or expert judgment, even when the information does not support the initial choice of course of action and re-examining the positive and negative consequences of all known alternatives, including those originally regarded as unacceptable, prior to making a choice" (Janis & Mann 1977). In this perspective, the raw data will be interpreted by functional managers. Project managers and experts contextualize the information depending on the project goals and consult functional managers to carry out the new tests, if necessary. Finally, the contextualized result of the tests will be presented to the steering committee. The last stage corresponds to Simon's model during which the steering committee, using a benefi t / risk analysis, will decide whether to continue or not.

In the fi rst two stages, the project managers more or less know which questions must be answered in order to obtain the authorization of commercialization (European Commission

Detailed vision

Figure 3 illustrate a detailed vision of decision-making in drug development projects. We use the Business Process Modeling Notation (BPMN), which is a st andard graphical not at ion. This diagram illust rat es t he int eract ions between the different actors and shows the fl ow of information from the top to the bottom of the pyramid and vice versa. We focus on the new information analysis stage of the decision-making process.

At the end of each phase, several options exist. If the results of studies are suffi ciently good and demonstrate the objectives of the phase such as effi cacy for animals in preclinical phase, the decision will be to continue or accelerate the transition to the next phase (tests on humans). If the results are not adequately satisfying, the steering committee, consulting the project team, requests to perform the new tests which clarify and complete the previous results. Depending on the situation, it is possible to postpone the Go / No Go decision waiting for the new results or to start the next phase and review the decision when the new results arrive. If the results are bad and prove the ineffi cacy or the toxicity of the molecule, the project will be stopped.

During the whole process, we fi nd examples of the three types of uncertainty factors. During the interpretation of data, the factors related to the object (molecule) play an important role in creating uncertainty, especially by incompleteness or contradiction of information. Factors related to subjects, especially individual factors, such as perception and reasoning are also important. During the contextualization of information, factors related to the context appear: internal factors, such as the condition of other projects in the pipeline and external factors such as market dynamics.

During t he represent at ion of information, the role of subjects in the communication of results is crucial. At the end, during the Go / No Go decision, factors related to subjects, especially collective factors, such as debates and different ideas about the doubtful results contribute to creating uncertainty. There are two major problems in such a human-in-the-loop system: the loss of information and the subjectivity of interpretation and representation, on the right-hand side of the pyramid. This descript ion helps us obt ain an understanding of the decision-making process, which is essential to improve these practices.

Application case

Many questions need to be answered to prove the safety, effi cacy, and quality of a molecule in order to obtain the authorization of commercialization. The toxicity of the molecule, its stability, clinical and side effects, mechanism of absorption and distribution in human body, and elimination from it are a f ew examples of t hese quest ions. In the decision pyramid, we consider the stability question as a part of the quality question: is the product stable under conditions of usage? Many environmental factors affect the stability of the product.

Depending on the project goals and also the available quantity of the product, the project team establishes a list of tests to be conducted in order to obtain data on product degradation in different climatic zones. Operational conditions such as temperature, humidity, and light are also determined, so that the real packaging and storage conditions are simulated. A protocol that includes this information and also the study number, quantity of the product, time intervals, measurement, and analysis methods have to be followed by technicians. Table 1 presents a simplifi ed part of the results. At time t 0 +12 months, technicians register -0,05% of degradation in ambient temperature.

The f unct ional manager's int erpretation is that our molecule is approximately stable. The project team contextualizes this interpretation in terms of project goals and tries to answer the following questions: does this degradation rate impact the effi cacy of the molecule in usage conditions? Could the degradation rate be reduced in another container such as a blister? In relation to the results of other studies, such as toxicity, is this degradation rate acceptable? Thus, after all these tests and studies, many questions remain without certain answers.

Conclusion

The comprehension of the notion of uncertainty is indispensable for understanding the decisionmaking process in situations where we do not have enough knowledge to decide. We distinguish two main approaches in defi ning uncertainty: the objective and the subjective approaches. We propose a new defi nition of uncertainty that allows these approaches to converge, including three key elements: subject, object, and context. From this point of view, we present a typology of uncertainty factors related to each element. This typology enables us to recognize and control some sources of uncertainty and offers a perspective to deal with causal and infl uential factors of uncertainty related to subject and context, which are less studied compared to uncertainty caused by object.

Decision-making systems in companies are the human-in-the-loop type systems. Thus, we cannot ignore the role of human factors in generating uncertainty and dealing with / handling it. In the description of the decision-making process in pharmaceutical industry we propose, the human aspect is in the center. We identify different levels of hierarchy in the decision-making system in a pyramid, highlighting the role of the subject and context in producing and dealing with uncertainty. In this pyramid, we illustrate the information fl ow in two directions: from the steering committee to the technicians and vice versa.

A practical example regarding the question of stability, as a small part of a larger question, the quality of the molecule, is presented. Many other questions have to be answered during the development project. Go / No Go decisions are based on these answers which are inexact and incomplete. This description is a fi rst step to understand why decision-makers postpone decisions in such situations. A more complete model that offers a global vision of the project will be the next step of this research work.

Figure

  Figure 1. Our typology of uncertainty factors

  2008). However, the hypotheses about the molecule are not yet verifi ed by the tests. Thus the factors related to the object (project, new molecule) play an important role in creating and processing uncertainty. But in the last two stages, we have to interpret, analyze, contextualize, and represent the acquired information and the role of the subjects (project manager and the experts) becomes crucial. A more detailed version is presented in the next section, emphasizing the last two stages.

Figure 2 .

 2 Figure 2. Global vision of decision-making process in drug development projects.

Figure 3 .

 3 Figure 3. Detailed vision of decision-making in drug development projects.

Table 1 .

 1 Stability measurement tests

	Time/ Temperature	0°5°25°t
	0	13 µg/l	13 µg/l	13 µg/l
	t 1 month	12,9999 µg/l	12,9999 µg/l	12,9995 µg/l
	t 6 months	12,9998 µg/l	12,9997 µg/l	12,9980 µg/l
	t 12 months	12,9997 µg/l	12,9995 µg/l	12,9935 µg/l
	t 1 month + H 2 O		12,9994 µg/l	12,9945 µg/l
	t 6 months + H 2 O		12,9993 µg/l	12,9942 µg/l
	t 12 months + H 2 O		12,9991 µg/l	12,9934 µg/l

Acknowledgements

This work was supported by the Foundation for an Industrial Safety Culture (Fondation pour une Culture de Sécurité Industrielle).

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