Cecilie Lukas Chabada
email: lukas.chabada@ntnu.no

Maria Damgaard

Heidi Carin Dreyer
email: heidi.c.dreyer@ntnu.no

Hans Henrik Hvolby

Iskra Dukovska-Popovska

Cecilie Maria Damgaard
email: cecilie@celog.dk

Hans Henrik Hvol- By

Logistical Causes of Food Waste: A Case Study of a Norwegian Distribution Chain of Chilled Food Products

Keywords: logistics, causes, food waste, distribution chain, chilled products

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Managing the physical flow of chilled products with short shelf life and sensitiveness to physical handling is challenging for the actors in the food distribution chain (FDC).

The FDC includes the wholesalers, stores and logistical and transport provides which takes part in the delivering of food to end customers. The main priorities are to make sure of short lead times and sufficient conditions during the physical distribution. In the food distribution chain products are being wasted stages [START_REF] Beretta | Quantifying food losses and the potential for reduction in Switzerland[END_REF][START_REF] Eriksson | Food losses in six Swedish retail stores: Wastage of fruit and vegetables in relation to quantities delivered[END_REF]. A study by [START_REF] Hanssen | Food Wastage in Norway[END_REF] revealed food waste of around 5-8% for chilled products at the retail stage in Norway. Such waste has economic, environmental and social impacts [START_REF] Mena | The causes of food waste in the supplierretailer interface: Evidences from the UK and Spain[END_REF]. Therefore, managers have an intention to reduce food waste. However, methods and concepts systematically approaching food waste reduction are scarce [START_REF] Garrone | Opening the black box of food waste reduction[END_REF]. This might be because food waste related costs have been undervalued or hidden [START_REF] Mena | The causes of food waste in the supplierretailer interface: Evidences from the UK and Spain[END_REF].

Identifying the causes of food waste is the first step towards food waste reduction. Studies by [START_REF] Mena | The causes of food waste in the supplierretailer interface: Evidences from the UK and Spain[END_REF], [START_REF] Beretta | Quantifying food losses and the potential for reduction in Switzerland[END_REF] or [START_REF] Muller | Food waste in Norway: Root causes analysis at the producer -retailer stage[END_REF] have indicated several causes of food waste. For example, as food companies strive for a high service level under varying demand, they often maintain too high inventories and safety stock levels, which subsequently lead to food waste. For food products, due to its perishable nature and restricted shelf life, it is significantly important that supply and demand is aligned and that the planning and control mechanisms are designed according the characteristics of the product, market and process involved. Until now, research on food waste has mainly focused on quantifying volumes, where in the food chain waste is created and what product category which most frequently is being created. The planning and control of the FDC and the effects on food waste is still area which needs to be explored in order to understand how food waste could be reduced.

The aim of this study is to explore logistical causes of food waste in the FDC of two types of chilled products; products with fixed shelf life and products with age dependent deterioration rates. The reasons for differentiating the products are the different planning and handling practices used for the above mentioned types, as similarly used by [START_REF] Bakker | Review of inventory systems with deterioration since 2001[END_REF]. The scope of this study is on food distribution chains in Norway, whose geography is characterized by long transportation distances, scattered population centers, and challenging climatic conditions which increase lead time and lead time variability [START_REF] Romsdal | Fresh food supply chains; characteristics and supply chain requirements[END_REF]. Since the phenomenon under study is relatively new, a case study research has been selected [START_REF] Yin | Case study research: Design and methods[END_REF].

Current research identifying causes of food waste is described in the section 2 followed by section describing methods of data collection and analysis. After that case description, findings and discussion on identified challenges in logistical planning and physical handling captured from interviews in case companies are presented. In the last chapter, several concluding comments are made and future work is proposed.

Connecting logistics and food waste

The main reasons for food being wasted is insufficient quality and expired date [START_REF] Mena | The causes of food waste in the supplierretailer interface: Evidences from the UK and Spain[END_REF]. Setting this in relation to logistics, it can refer to time and quality which are among the main performance indicators of logistics [START_REF] Shapiro | Logistics Strategy: cases and concepts[END_REF]. According to APICS (2013) logistics system consists of planning and coordination of the physical movement aspects of a firm's operations such that a flow of raw materials, parts, and finished goods is achieved in a manner that minimizes total costs for the levels of service desired. finished food products that are manufactured, wholesaled and retailed but not sold to the intended customer or which are sold but to a price lower than the intended price due to insufficient quality or short remaining shelf life. For example discounts due to short remaining shelf life are considered as waste. The intended customer for the wholesaler is the store and for the store the intended customer is the paying consumer.

For in-depth analysis of food waste and its logistical causes a need for locating food waste in the processes of the FDC has been recognized. [START_REF] Eriksson | Food losses in six Swedish retail stores: Wastage of fruit and vegetables in relation to quantities delivered[END_REF] defined two main types of food waste in the stores on the process level, namely in-store and pre-store food waste. This study extends on their work and adds transportation and in-warehouse food waste to the analysis (see Fig. 1).

Fig. 1. Categories of food waste in the food distribution chain

In-warehouse food waste includes all food products wasted during the processes in the warehouse of the wholesaler. Transportation food waste includes the food waste created during transportation between wholesaler and stores. Pre-store food rejections include food products rejected by the store within 24 hours after delivery. After this period it is considered as in-store food waste. This waste belongs to the supplier in accounting terms, but usually becomes physical waste at the store [START_REF] Eriksson | Food losses in six Swedish retail stores: Wastage of fruit and vegetables in relation to quantities delivered[END_REF]. Finally, in-store food waste includes all products wasted inside the store.

The number of studies identifying the causes of food waste at different stages of the food supply chain in different countries has increased during the last couple of years. Mena, Adenso-Diaz, and Yurt (2011) have looked at the causes of food waste in the supplier-retailer interface at British and Spanish companies. They categorized the causes into mega-trends, natural constraints and management root causes where only the latter can be fully under the control of the managers, and includes issues such as inaccurate planning and forecasting, poor information sharing, poor ordering, poor handling or poor promotions management. Similarly, Muller (2013) presented a root cause analysis of food waste in Norwegian food supply chains. In that study, overproduction and over-ordering, large distribution packages, high inventory levels, inappropriate stock rotation or inadequate handling have been among the mentioned logistical causes of food waste. Finally, Beretta et al. (2013) presented causes of food waste considering the whole food supply chain in Switzerland, and categorized the causes into avoidable, possibly avoidable and unavoidable considering. They mention overproduction or high stock levels among the avoidable causes. All of the above mentioned studies indicate that food waste could be reduced by better planning and handling of logistical activities. Since the current studies present mainly qualitative data of different causes on quite an aggregated level one can only assume, based on the frequency of evidence, that planning has a greater impact on food waste than physical handling. Moreover, the studies indicate that physical handling, decisions made by planners, and data used during the planning process could have an impact on food waste. This study investigates for the evidence of food waste causes in the case companies that can support these hypotheses.

Methods for data collection and analysis

Investigation of logistical causes of food waste is still an unexplored area, therefore, this study undertook the case study approach outlined by Yin (2009). Case companies have been selected based on their relatively high impact in the Norwegian market. Different quantitative and qualitative data has been collected to identify causes of food waste in the case companies. Quantitative data showing the redistribution of the main causes has been collected for in-warehouse food waste and pre-store food rejections since the wholesaler is the only company that registers them. The in-house ERP system and the internal documents of the wholesaler have been used for this purpose. Since the data is registered differently in pieces, boxes and kilos depending on the product type, financial losses have been used to compare the relative values of registered causes. Quantitative data aggregates amounts from a 12 -month period and consider food waste as defined by the case companies and not as defined in the section 2. The impact of different causes has been analyzed in relation to the total food waste.

Second, qualitative data supplements the quantitative findings by discussing underlying causes of the main causes identified in the case companies. The data has been collected via semi-structured interviews, mapping and personal observations of planning and handling processes. Causes of transportation and in-store food waste have been collected via interviews and observations at two transporters and three stores. In order to highlight the main problematic areas the identified underlying causes of food waste were grouped using the fishbone diagram [START_REF] Stevenson | Operations management[END_REF].

The scope of the investigation is on chilled products, as these have been identified as the main wasted category [START_REF] Gustavsson | Global food losses and food waste[END_REF]. This study includes product groups like dairy, meat, fish, fruit and vegetable products (F&V) and the main focus is on the planning and handling causes of food waste in the FDC. During the study it has been recognized that planning and handling practices of products with fixed shelf life varies from products with age dependent deterioration rate, therefore this study differentiates between these two categories when discussing causes of food waste. Products with fixed shelf life are wasted when the due date is exceeded or close to be exceeded. Besides F&V, majority of chilled products have fixed shelf life. Products with age dependent deterioration rate are wasted when the quality is perceived to be insufficient. The majority of F&V have an age dependent deterioration rate.

Case description and findings

The wholesaler is a major wholesaler in Norway distributing around 5500 products. Three stores are direct customers of the wholesaler consisting of one store with low and two stores with high turnover. Together with two transportation companies delivering food products between the wholesaler and the stores the companies are part of the same supply chain. First analysis of data indicates 90% of food waste in this FDC comes from wasted chilled products. Two main causes of food waste are registered at the wholesaler, namely insufficient quality and short remaining shelf life. Quantitative data on causes of food waste revealed that in two thirds of cases of in-warehouse food waste of products with fixed shelf life, short remaining shelf life is the main cause leaving one third for damaged products. In more than 90% of cases the main cause of in-warehouse food waste for products with age dependent deterioration rate is insufficient quality (this information comes from discussions with planners and operators in the warehouse). Similar findings can be observed for pre-store food rejections where 96% of products with age dependent deterioration rate have been rejected by stores due to insufficient quality while 64% of products with fixed shelf life have been rejected due to short remaining shelf life (see Fig. 2).

Fig. 2.

Registered causes of pre-store food rejections Fig. 2 also illustrates that around two thirds of food waste come from products with age dependent deterioration rate. This might be due to several reasons like different biological deterioration rate of products, higher margin or different planning and handling procedures of products with age dependent deterioration rate and fixed shelf life. Analysis of causes of food waste registered at the wholesaler revealed that "insufficient quality" represents mainly handling failures and "short remaining shelf life" represents mainly planning failure when considering food products with fixed shelf life. Based on this, logistical planning seems to have higher impact on financial losses than physical handling of products with fixed shelf life.

Causes of insufficient quality and short remaining shelf life

Company visits and interviews with planners and operators confirmed the existence of food waste categories defined in Fig. 1. Moreover, several underlying causes of insufficient quality and short remaining shelf life have been revealed. These are discussed in this chapter per food waste category, supported by previous studies when relevant.

In-warehouse food waste of products with fixed shelf life is mainly created due to short remaining shelf life. As the potential underlying causes have been pointed high inventory and safety stock levels, and quite aggregated planning and coordination of promotions with stores. For promotions the stock levels are set high in order to prevent stock outs and because demand is unpredictable, thus increasing food waste. Food waste is also increased due to product cannibalization [START_REF] Taylor | Demand management in fresh food value chains: A framework for analysis and improvement[END_REF]. Ordered amounts are sometimes increased also due to low ordering frequency and big batch sizes, when the wholesaler orders more than is needed to fit the batch size. In- Products with age dependent deterioration rates have insufficient quality as the main registered cause of food waste. This is expected as most of the products do not have due dates to be judged by. Many of the underlying causes are, however, similar as for products with fixed shelf life. An additional planning challenge for products with age dependent deterioration rates is considering their quantity and quality levels, and remaining shelf life of such products in the planning decisions. This is mainly due to missing technology that would allow visibility of such information and that would utilize them to increase the accuracy of future demand or safety stocks. Better utilization of barcodes or RFID (radio frequency identification) technology for capturing additional data about products in the ERP system could reduce food waste.

Typical handling causes of food waste discovered in the warehouse are damages caused by the operators when picking the products or transporting them to the storage. Additionally, pallets with temperature sensitive products are sometimes kept waiting in the area with inappropriate temperature levels. Alternative layout organization or training of operators could improve the physical handling of such products.

Transportation food waste created for both products with fixed shelf life and age dependent deterioration rates is mainly due to inappropriate handling during the loading and unloading process or during the transportation. Among the main challenges is the organization of pallets inside the trucks with frozen and chilled temperature zones, mostly organized based on the order of the stores. Temperature sensitive products placed against the isolated partition panel between two temperature zones, or against an outer wall whilst outside temperatures are very low might be exposed to either too low or high temperatures, thus reducing quality level. This is an even bigger challenge for deliveries to distant stores with longer delivery times. Including information about product sensitivity in route planning could identify optimal trade-offs between space allocation and potential level of food waste created in different scenarios.

Pre-store rejections occur mainly due to insufficient quality (products with age dependent deterioration rate) or short remaining shelf life (products with fixed shelf life). The underlying causes lie at the wholesaler warehouse. For example, time and quality decrease for products that are picked at the stock of the wholesaler and kept in the temporary waiting area before they are dispatched to stores. The temperature in the temporary area is either higher or lower than is required by the products and the time spent in this area sometimes exceeds two days. This information is, however, not considered when planning the picking orders and deliveries to stores. Pre-store rejections could be thus reduced by considering the shelf life, waiting time and temperature information during the planning and control of deliveries in the warehouse. This would consequently lead also to saving additional transportation and disposal costs.

In-store food waste of products with fixed shelf life and products with age dependent deterioration rate is created due to similar reasons. From a planning perspective it is lack of data captured and utilized in replenishment process that causes the most problems. Information about current volumes or expiration dates of products in shelves are checked only manually without using suitable information technology that captures and utilizes the mentioned data. Forecasts and safety stock levels are therefore calculated only based on an experience of planners who sometimes consider historical sales. High order and delivery frequency allow high turnover stores to plan without very precise forecast. For the smaller stores higher ordering frequency and smaller batch sizes could reduce food. Capturing and utilizing data about the current product volumes and remaining shelf life of the products in the shelves could increase visibility of the products, and reduce uncertainty and food waste. Other causes of instore food waste have been indicated mechanical damages caused by customers or operators. Utilizing equipment ensuring the right temperature and display of the products in the shopping area could lead to reduction of mechanical damages in the stores.

The above discussed causes are summarized and grouped in the fishbone diagram under four areas, namely planning decisions, data utilization, execution of plan and damaged products, in order to highlight the main problematic areas (see Fig. 3).

Food Waste

Data utilization

Planning decisions

Product damage Execution of plan

Conclusion

The study presents the main and underlying causes of food waste for products with fixed shelf life and age dependent deterioration rates as identified in the case companies. The underlying causes of food waste are structured into four areas, namely planning decisions, data utilization, execution of plans, and damaged products. More research is necessary to validate the findings of this study. Some of the identified causes might not be that relevant for other countries. For example, companies in other countries might be able to cope with low delivery frequency or big batch sizes better than companies in Norway, as they do not face the challenges such as long delivery lead times or long distances traveled due to fjords, ferries or temporary closed roads during the winter period. Future research could focus on deeper analysis and quantification of identified causes in order to understand the relative impact of individual causes on food waste and so to better identify improvement options. The main focus could be on quantifiable causes of food waste as forecasting accuracy, inventory and safety stock levels and promotions which have been highlighted also by other researchers. Fur-thermore, trade-offs between food waste and availability should be investigated and discussed. The study contributes to the literature by in-depth analysis of quantitative and qualitative data on planning and handling causes of food waste in the FDC which is still rare in the current research. Practitioners in a similar industry may use the findings as a baseline for identification of food waste causes in their companies.

Fig. 3 .

 3 Fig. 3. Planning and handling causes of food waste

Acknowledgement. Authors of the paper would like to express a deep gratitude to the case companies involved, to the researchers Peter Falster and Chris Martin, and to research organization NordForsk which funds the LogiNord project.


Stefan Wiesner

Christian Gorldt

Mathias Soeken

Klaus-Dieter Thoben

Rolf Drechsler
email: rolf.drechsler@dfki.de

Requirements Engineering for Cyber-Physical Systems

Keywords: Requirements Engineering, Industrie 4.0, Cyber-Physical Systems, Natural Language Processing, MSEE Integrated Project

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Three industrial revolutions have led to paradigm changes in the domain of manufacturing so far: mechanization through water and steam power, mass production in assembly lines, and automation using information technology. However, for the last years researchers and policy makers have increasingly advocated an upcoming fourth industrial revolution. For example, the German government promotes the computerization of manufacturing industries in their "Industrie 4.0" program [START_REF] Kagermann | Deutschlands Zukunft als Produktionsstandort sichern-Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0[END_REF], while in the United States the Smart Manufacturing Leadership Coalition (SMLC) facilitates the broad adoption of manufacturing intelligence [START_REF]Implementing 21st Century Smart Manufacturing[END_REF]. In order to follow these trends, elements like machines, storage systems and utilities need to be able to share information, as well as act and control each other autonomously. Such systems are called Cyber-Physical Systems (CPS) [START_REF] Baheti | Cyber-physical systems[END_REF]. CPS emerge through the complex networking and integration of embedded systems, application systems, and infrastructure, enabled by human machine interaction. In contrast to conventional systems used for production or logistics, they can be seen as systems of systems, which require the collaboration of different disciplines such as mechanical engineering, electrical engineering, and computer science for their realization [START_REF]agendaCPS: Integrierte Forschungsagenda Cyber-Physical Systems[END_REF].

For the development of today's conventional production systems, methods and tools from the field of systems engineering are applied, which deal with the development of complex solutions, consisting of a large number of components whose interactions shall produce a desired result [START_REF] Sage | Handbook of systems engineering and management[END_REF]. Systems have to be both appropriate and cost effective [START_REF] Kossiakoff | Systems engineering principles and practice[END_REF], which makes understanding the requirements of the customer and other affected stakeholders a prerequisite for successful systems engineering [START_REF] Elgh | Modelling and management of manufacturing requirements in design automation systems[END_REF]. They are needed for planning the development process, assessing the impact of changes and testing the acceptance of the outcomes [START_REF] Hull | Requirements Engineering[END_REF]. Inadequate Requirements Engineering (RE) is one of the main sources for the failure of development projects and culminates in exceeding budgets, missing functionalities or even the abortion of the project [START_REF] Hauksdóttir | Identification of a reusable requirements structure for embedded products in a dynamic market environment[END_REF]. Consequently, in concordance with the principles of concurrent engineering, RE continues along the development process of a system and secures a consistent and traceable elicitation and management of requirements. There is an ongoing interaction between RE and the development phases in systems engineering [START_REF] Hull | Requirements Engineering[END_REF].

Therefore, adequate RE is also the key to success or failure of every CPS development project. However, CPS differ from conventional production systems in various aspects, leading to new challenges for the RE process. CPS are open systems, which have to be aligned with dynamic user needs in a global context. Furthermore, requirements towards CPS underlie evolutionary changes. The scope and emphasis of the relevant requirements change with respect to the final application and environment of the CPS [START_REF]agendaCPS: Integrierte Forschungsagenda Cyber-Physical Systems[END_REF]. Finally, CPS are based on integrating hardware, software, and service components, covering the whole life cycle, from ideation to decommission. The required competencies for CPS development and their support in all life cycle phases have to be included through collaboration with partners from the different disciplines [START_REF] Blanchard | System engineering management[END_REF].

The objective of this paper is to elaborate the specific challenges of RE for CPS in detail and give first recommendations for their solution. Therefore, in Section 2 the state-of-the-art in CPS and systems requirements engineering is described. Based on this theoretical background, the detailed challenges are extracted from a literature review in Section 3. Natural Language Processing (NLP) is used as an approach to overcome the language barriers between the involved disciplines in Section 4. The conclusion in Section 5 gives an outlook, how a comprehensive RE methodology for CPS could be developed.

Theoretical Background

In this chapter, the main characteristics of Cyber-Physical Systems are explained, followed by the state-of-the-art in Requirements Engineering for systems, in order to be able to identify the challenges of RE for CPS.

Cyber-Physical Systems

Cyber-Physical Systems (CPS) can be seen as systems of integrated computational elements interacting with physical entities. In contrast to embedded systems where the focus is more on the computational elements, CPS emphasize the link between the computational and physical elements. In this sense, CPS represent a network of interacting elements with physical input and output instead of as standalone devices. CPS are therefore complex systems and can be characterized by five distinct characteristics [START_REF]agendaCPS: Integrierte Forschungsagenda Cyber-Physical Systems[END_REF].

1. Merge of physical and virtual world: CPS involve a multitude of parallel and interlinked sensors, computers, and machines, which collect and interpret data to decide on this basis and control real world physical processes. Thus, systems engineering needs to integrate industrial process and control systems with information technology [START_REF] Rajkumar | Cyber-physical systems: the next computing revolution[END_REF]. 2. System of systems with dynamic system borders: Depending on application and task, different CPS are arranged into a system of systems for a limited time. Consequently, CPS have to be able to actively configure services and networks with other systems or parts of systems, which may be unknown in the beginning, and provide new and composite components and services in a controlled way [START_REF] Colombo | A system of systems view on collaborative industrial automation[END_REF]. 3. Context-aware, partially or fully self-governed, with active control in realtime: Relating to their specific task, CPS use the relevant services to capture their application environment and situation to coordinate a useful and valuable system behavior for all involved stakeholders. This requires continuous monitoring and assessment of environmental and application data [START_REF] Wan | Context-Aware Security Solutions for Cyber Physical Systems[END_REF]. 4. Collaborative systems with distributed and alternating control: The CPS has to be able to perceive and assess the situation, the activities to be executed and the local and global goals of the actors. Decisions are based on this information and lead to a cooperative learning process [START_REF] Zhou | Advanced Control Technologies in Cyber-Physical System[END_REF]. 5. Comprehensive human-system interaction: CPS have to incorporate human behavior also on a physical level, which requires the use of sensor and actuator technology, e.g. in the form of artificial limps. This leads to an extension of the human capacity to act and human cognition, supported by multimodal control interfaces, recognition, and interpretation of human behavior and interactive decision making between the system and single persons or groups [START_REF] Schirner | The future of human-inthe-loop cyber-physical systems[END_REF].

Systems Requirements Engineering

Requirements define the needs of organizations, groups, or people along with their surroundings and describe what a solution must offer in order to satisfy those needs. Their formulation, documentation, and maintenance are the main objectives of Requirements Engineering. It describes "a process, in which the needs of one or many stakeholders and their environment are determined to find the solution for a specific problem" [START_REF] Nuseibeh | Requirements Engineering: A Roadmap[END_REF]. Systems engineering involves RE as an independent activity not restricted to a specific development phase or project. There is an ongoing interaction RE and the development phases in systems engineering, as can be shown with the V-Model [START_REF] Rausch | Das V-Modell XT -Grundlagen, Erfahrungen, Werkzeuge[END_REF] in Fig. 1: Requirements engineering in the V-Model, according to [START_REF] Hull | Requirements Engineering[END_REF] Fig. 1 shows the activities performed during the individual phases of system development in separate layers. Requirements are important for all layers in systems engineering. It is necessary to validate requirements from lower layers against requirements from upper layers and the stakeholder needs in order to check that the requirements represent the original goals for the system development. Furthermore, the design and implementation of the system has to be verified to check that it fulfills the requirements. In order to support the different tasks, the specification of requirements has to follow several contradictory objectives. To minimize the time to write requirements and make them understandable for all of the involved stakeholders, often an informal approach is used without any constraints on how requirements are specified e.g. in natural language. However, to minimize the time needed to validate requirements and verify the system design, a formal specification is required. Abstract semantics and syntax enable automatic checks like formal verification. Often a trade-off between formal and informal specification is implemented, e.g. by using controlled languages [START_REF] Funk | CLOnE: Controlled Language for Ontology Editing[END_REF] or boilerplate techniques [START_REF] Farfeleder | DODT: Increasing requirements formalism using domain ontologies for improved embedded systems development[END_REF].

Qualification

Challenges of Requirements Engineering for Cyber-Physical Systems

In their research agenda for CPS, Geisberger and Broy [START_REF]agendaCPS: Integrierte Forschungsagenda Cyber-Physical Systems[END_REF] identify engineering challenges for Cyber-Physical Systems. They emphasize the central role of Requirements Engineering for CPS development, integration, maintenance and evolution. Involving users and other stakeholders from different domains actively into CPS development from the beginning and adaption of CPS to needs, habits and competences of the users, would require a more informal approach for requirements specification. However, the specification of formal requirements models is requested for detailing of requirements and mapping them to system elements, integration of mechanical engineering models with digital models from software and systems engineering for the collaborative description of requirements, as well as their implementation, validation, evolution and communication between stakeholders from different disciplines.

Penzenstadler and Eckhardt [START_REF] Penzenstadler | A requirements engineering content model for cyber-physical systems[END_REF] agree that ensuring communication and consistency of requirements for CPS is a challenge due to the variety of stakeholders involved. Furthermore, viewing CPS as a system of systems, the independence of the constituent systems and their evolutionary nature leads to exceptionally distributed RE activities for a multitude of stakeholders with isolated RE approaches. The authors propose a RE content model for requirements elicitation and documentation at different levels as a solution. However this requires the adoption of a formal model by all stakeholders involved. Ncube [START_REF] Ncube | On the Engineering of Systems of Systems: key challenges for the requirements engineering community[END_REF] focuses on the systems of systems aspect. RE needs concepts and techniques to specify key interoperation influencing requirements. Furthermore, the complexity of systems of systems leaves requirements fragmented among many disciplines and sometimes conflicting, unstable, unknowable or not fully defined. Finally, the properties of systems of systems emerge from the cumulative interactions of the single systems. Therefore, RE methods and tools have to be able to verify emergent effects against requirements with predictable results.

The analyzed literature shows that Requirements Engineering for CPS creates specific challenges, especially for requirements specification and verification. On the one hand, a way has to be found to involve the system user into the development process and dynamically exchange requirements between a multitude of stakeholders from different disciplines. This demands for a more informal, generic requirements specification. On the other hand, for the identification of the system elements and emergent effects for the verification of requirements, more formal and domain specific modeling of requirements is needed. A solution could be the application of both, formal and informal requirements specification, connected by a (semi-)automatic translation. Natural Language Processing (NLP) could be used in such an approach.

Natural Language Processing

The CESAR project provides an overview of different Requirements Specification Languages (RSL) for systems engineering, according to their degree of formality [START_REF]CESAR: Cost-efficient Methods and Processes for Safety-relevant Embedded Systems[END_REF]. In textual form, formality is increased from Guided Natural Language, over boiler-plate RSL up to pattern based RSL. Guided Natural Language specifications are achieved by checking free text descriptions with a domain specific dictionary, highlighting ambiguous terms. Boilerplates are pre-formulated requirements, which are parameterized to describe stakeholders, capabilities or attributes, while patterns use a stronger formalism with fixed semantics. In graphical form, SysML is a visual modeling language for system design based on UML, which can cover multiple degrees of formality with its various underlying diagrams.

In the development of large and complex CPS one is highly interested in a high degree of automation. This becomes accessible, although not easy, when formal descriptions are used that are readable by machines. Conversely, formal descriptions are often not accessible for end users and differ heavily between the disciplines involved in CPS development. The most basic format, understood by the end user and all stakeholders is natural language. Therefore, at higher levels of abstractions, e.g. for stakeholder and system requirements, most of the descriptions are given in natural language text. However, they are therefore barely accessible for automation.

Natural language processing techniques can be utilized to overcome this problem and support requirements exchange between the system user and the stakeholders in CPS development. Several algorithms and tools for syntax [START_REF] Jurafsky | Speech & Language Processing[END_REF] and semantics analysis [START_REF] Miller | WordNet: A Lexical Database for English[END_REF] have been proposed for this purpose. Due to ambiguities that are contained in natural language one needs to take into account a trade-off between the degree of automation and the restrictions that are assumed on the text. In order to achieve 100% automation, all ambiguities need to be avoided which can e.g. be achieved by controlled languages [START_REF] Funk | CLOnE: Controlled Language for Ontology Editing[END_REF] or boilerplate techniques [START_REF] Farfeleder | DODT: Increasing requirements formalism using domain ontologies for improved embedded systems development[END_REF]. This comes to the cost of basically learning a new language, which may not be practical implementable when texts are written by many stakeholders from different disciplines, which prohibits the application of domain specific ontologies or boilerplates.

Alternative approaches employ a dialog system between the designer and the machine in order resolve possible ambiguities [START_REF] Drechsler | Towards Dialog Systems for Assisted Natural Language Processing in the Design of Embedded Systems[END_REF]. The machine tries to process as much information as possible automatically and whenever no reliable conclusion can be implied the designer is asked for assistance. This approach has e.g. been used to extract formal models in UML or SysML to represent structure from natural language use case scenarios [START_REF] Soeken | Assisted Behavior Driven Development Using Natural Language Processing[END_REF]. Also for translating natural language requirements to formal expressions, NLP techniques have been used [START_REF] Soeken | Automating the Translation of Natural Language Assertions Using Natural Language Processing Techniques[END_REF]. Finally, NLP techniques can assist specification engineers when writing texts. Simple techniques such as spell checking and grammar checking are already common practice in state-of-the-art word processing applications. Techniques that go beyond these are the automatic detection of requirement sentences, measuring the clarity of a sentence, or measure the validity of the sentence with respect to specification guidelines.

The application of NLP to Requirements Engineering for CPS could help to solve some of the challenges identified in the previous section. User involvement would be supported, as requirements and validation feedback could be informally specified in natural language and callback in the case of ambiguities. Furthermore, information exchanged between stakeholders of different disciplines, e.g. in requirements workshops, could be semi-automatically transformed into the correct formal models for each discipline involved.

Conclusion

The development of CPS creates new specific challenges for Requirements Engineering, in contrast to conventional production systems. Relevant characteristics of CPS that have to be observed are the integration of physical and virtual elements, the constitution of CPS as systems of systems, context awareness, distributed control and human-system interaction. This results, on the one hand in intensified user collaboration and on the other hand in the involvement of many different disciplines during system development. In spite of distributed RE activities, communication and consistency of requirements have to be secured. Interoperability of the CPS elements has to be guaranteed by specific requirements. Dynamically changing and emergent behavior must be included in the CPS specification. Natural language could be used as an informal requirements specification for exchange between the system user and stakeholders from various disciplines, but is often unclear and ambiguous. Furthermore, it can barely be handled automatically. As an approach to keep natural language as the form to exchange requirements, while still having unambiguous and automatically processible formal specifications, Natural Language Processing is proposed. The application of NLP could establish a dialog system, which supports resolving ambiguities and semi-automatically transform requirements in natural language into formal domain specific models. Further research in this area will be conducted to concretize NLP application in RE for CPS and propose first practical methods and tools.

Fig. 1 .

 1 Fig. 1.Requirements engineering in the V-Model, according to[START_REF] Hull | Requirements Engineering[END_REF]

Acknowledgements. This work has been partly funded by the European Commission through the FoF-ICT Project MSEE: Manufacturing SErvice Ecosystem (No. 284860) and the German Federal Ministry of Education and Research (BMBF) through the project SPECifIC (01IW13001).


Patrik Urban
email: patrik.urban@vsb.cz

Lenka Landryová
email: lenka.landryova@vsb.cz

Alarm Management at Operators Workstations

Keywords: Urban, Lenka Landryová Alarm, System, Management, HMI, Automation

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction to Techniques Applied for Work of Operator Workstations

Operators of control systems work in a field, in which emerging technology is characterized by features allowing implementation of control into processes without direct human intervention. However, automation and supervisory control do not fully exclude all human activity, those who supervise the automatic work of machines, in which it is still required to participate in a task for machine setup, the program upload, optimization of processes and similar areas.

Component object model techniques and serverclient architecture

The technology, which has enabled bringing data to an operator workstation, is based on the principle of object-oriented modeling, which allows two or more components of applications to cooperate with each other even if they are created in different programming languages and designed for the use in different operating systems. This Component Object Model (COM) technology works on the serverclient communication principle, where the server sends data only when the client requests them, and uses the already mentioned object-oriented architecture, which brings one of the advantages of the "encapsulated" feature of programs into reusable software components that allows them to hide data and functions into the objects.

The object is an instance of a class, which is linked to a set of member functions and data. The component is a part of the program in a binary form, and as such, it must meet a certain binary standard. As already mentioned above, this object can be connected to different applications or other program components. Due to the packaged data and functions of the object, the client does not care about the internal implementation but the external object behavior, for example, the provided functions, which are defined for the application by COM technology [START_REF] Bajgar | Administration of alarm events with the use of OPC object technology[END_REF].

Communication standards in control systems

Integration of business plans and the control systems in the industry would not be possible without standards developed for their communication. Manufacturers rely on the use of Supervisory Control And Data Acquisition (SCADA) or Distributed Control Systems (DCS) to implement their plans into production. This is enabled by open and effective communication architectures with OLE (Object Linking Embedding) for Process Control (OPC) standard, which focuses on data access and not the data type.

The idea of the OPC server is implemented into OPC Historical Data Server, as well as Alarm & Event Handling Server. OPC is a standard for both hardware providers and software developers. It provides a standard mechanism for the transfer of data from hardware devices to any client application, the highly optimized communication of software applications with the data sources, and it defines a mechanism for efficient data exchange between software and hardware.

Together with OPC interface allowing any client to access their device using OLE and COM techniques allow developers to use software components in their programs written in different languages.

Hierarchy of Industrial Control

The industrial control systems work in a hierarchical structure and consist of levels, see Fig. 1 [START_REF] Bajgar | Administration of alarm events with the use of OPC object technology[END_REF]:

 The level of direct control, from where "smart" sensors and smart devices provide the system with their data through the interface. This data collected from the equipment together with its configuration parameters are presented to the software applications.  Process level, where the data is used by DCS and SCADA systems with Human Machine Interface (HMI). The user of these systems is able to monitor, manage and evaluation processes, from which the data are obtained and can be further used at the information level.  Information level, where data are analyzed and processed by tools and used for management and information systems or economic applications. At this level the users are able to work and connect with SCADA software, databases, word processing, spreadsheets in conjunction with the production system.

Services of Control Systems

The service is the OPC server concept, which allows many different OPC servers to be placed under one common server that unifies access to data from different sources.

This common server provides one set of OPC compliant interfaces, eliminating the need for client applications to know which OPC server to use for each data item.

The service provides an interface compatible with OPC client applications to use the data. In this case, the control system is designed in functional hierarchical structure for each manufacturing operation and the procedural parts (involving equipment such as engines, tanks, etc.). This enables operators to configure an alarm system, a basic operator support system for managing abnormal situations, and create a simple alarm list of each monitored variable. The control system automatically adds the alarm from an object into a specific section in each alarm list.

It's a very effective and fast way from the point of view of cost, and also easier for operators, who are able to monitor "their" alarms, alarms in their competence under their login into a system, and not long unsorted list of alarms of all control systems. When a new alarm appears, it is added to the functional structure of the object automatically. Operators can monitor unacknowledged alarms recorded in the event list. The visible part of the control system alarm list also contains a "live tracking values" feature, which displays actual values and parameters that triggered the alarm, for example when the level in the tank falls below a certain minimum.

In the list it can also be seen, what the current value of a monitored variable is, which carried out the alarm. This feature can be identified as Alarm Grouping, meaning drawing up lists of key attributes, and thus creating manageable lists. The result is the one alarm in the alarm list for all alarms in the whole group presented to the operator screen.

Fig. 2. A Single Alarm List

This example shows how alarm grouping can help operators better understand the implications of a particular alarm in the control system, and its impact on the process. In systems without this feature, the decision and resolution of the alarm conditions rely on the knowledge of an operator, and under circumstances when several processes are monitored at the same time it is quite time consuming and/or risky.

Alarm Issues which Operators deals with in Control Systems

The basis for the work is to describe the situation and processes in which the alarm system is deployed. The correct description of the system facilitates further work with alarms and their management. An important idea of the methodology is a combination of the qualitative and quantitative approach to the research applied to the alarm system development. Data collection in the form of alarm records from different applications and process systems help us to find weaknesses in the management of alarms.

The data here are evaluated from two different process systems, resulting in a different number of events in them. This also shows that it is necessary to obtain the largest amount of findings possible to be able to evaluate better the management of alarms. The first records are taken from 15 minutes of monitoring, during which 27 alarms came, 25 of which were alarms on values exceeding the limits, and 2 were system failures alarm in first control system. Another system was examined as well and for the same period of 15 minutes the operator received 500 events on the workstation screen. This is an increased burden for the operator. Of the 500 events, 433 events were acquired as changes of monitored values and confirmed alarms, remaining events were alarms that showed an exceeded limit of 25 monitored variables, and a group of other system alarms, which consisted of changes in the valves/actuators of manual → automatic mode, a small change of reference values, changes from true → false values of binary variables.

Rationalization of alarm issues, listed in Table 1, should help operators manage stressful situations. The objective of configuration of the alarm management system is to allow operators to remove standing or nuisance alarms that are re-occurring on the main alarm list of their screens. Therefore two functions were configured for the above mentioned control system: Alarm Hiding and Alarm Shelving. Alarm shelving lets operators decide whether or not to put an alarm 'on the shelf' for a defined period of time or a certain occurrence. This temporarily removes it from the main alarm list to a special list, but the alarm itself is not affected. It will later require attention from the operator. In the meantime, the operator can concentrate on tasks judged to require their immediate focus. The question remains if alarm shelving makes a valuable and much-appreciated tool that helps operators work with maximum efficiency. The shelving is time limited to prevent important alarms to be removed or forgotten Alarm hiding is set up during the engineering phase. Its main purpose is to suppress alarms that are either expected or not relevant in a particular situation, or that are based on a known process state, e.g. low temperatures or flow during a controlled shutdown. As the name suggests, 'hidden' alarms are never visible to operators. They only see alarms that require action on their part.

Conclusion

Automation is the field, in which modern technology is being developed, characterized by features allowing implementation of control processes without direct human intervention. However, automation and supervisory control do not fully exclude people, who supervise the direct work of machines. The motivation for the research is fill in the gap between practicethe daily operation of operators supervising control systems, and an analysis of such processes. As an example of supervisory control we describe here the area of an alarm management system. Such system is dealing with alarm logs giving a feedback for better understanding at the level of the humanmachine interface in order to improve and support the engineering work on the design, configuration and implementation of the system for an operator supervising the production and managing alarms. As the production processes get very complex, there are increasing numbers of things, which can go wrong when controlling them. This research was also aimed to find out about the alarms from actual cases, how they are defined, what types are used, and how much their configuration in practice matches the ISA 18.2 standard, which defines alarm management for conditions in different control systems. The operators who are the immediate users and the engineers who configure the control systems features at the site during their implementation need to cooperate. The evaluation of process alarms in the control system from system operator point of view was described. Alarms are displayed, depending on whether the configured monitored variable exceeds the set limits. The alarm prioritizing during their configurations and design in terms of the frequency for requests for alarm acknowledgement by a single operator and alarm handled by operators during stressful situations remains a big task of control systems engineers to prevent hazardous consequences.

Fig. 1 .

 1 Fig. 1. Control System Hierarchy

Fig. 3 .

 3 Fig. 3. Alarm Grouping Tool Applied for Alarm List

Table 1 .

 1 Alarm Issues(Atkinson, T. , 2011)

	Alarm	Symptoms	Effects		Implications
	Issues
		High number of alarms	Devaluing of the Alarm	Texaco Milford
	Load Alarm	per operator per minute, 1 per minute is unac-ceptable, Highest seen 40 per mi-nute,	System Decision making impaired Poor operator responses Adds to operator stress Masks high priority alarms	Haven Alaska Slope Esso Longford North explosion
		Operators accept alarms	More outages
		without review	Loss of protective layer
		High number of alarms	Incorrect/delayed diagno-	Three	Mile
		from a single cause e.g.	sis of causal event	Island
		Compressor trip	Incorrect response to inci-
		Shutdown/Startup	dent
		Often see 100+	Delayed response to inci-
	Alarms Burst	Occasionally see 500+	dent Miss key alarms hidden in list E.g. failure to shut down safely
			Poor operator 'situational
			awareness'	following
			event
			Increased likelihood of
			subsequent errors


Mohamad Degoun
email: mohammed.degoun@emines-ingenieur.org

A Drissi
email: a.drissi@ocpgroup.org

Pierre Fenies
email: pierre.fenies@u-paris10.fr

Vincent Giard
email: vincent.giard@dauphine.fr

K Retmi

J Saadi

S A M Degoun

& J Saadi

General Use of the Routing Concept for Supply Chain Modeling Purposes: The Case

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The purpose of this paper is to analyze the solutions to the methodological problems that arose in the first phase of our research aiming to create a dual decision-making support system (DMS) dedicated to Supply Chain management and management control system. This phase has to do with gathering and formalizing the required knowledge to design simulation models on which to base the DMSs. Supply Chain (SC) generally refers to the logistics chain of multinationals. The different subsidiaries of these companies participate in the SC, both from within the organization, and as « satellites » involving multiple third party providers of logistics services and sub-contractors whose operations are coordinated by the multinational company [START_REF] Lee | Information distortion in a Supply Chain: the bullwhip effect[END_REF].

The SC object of our study is that of Cherifian Office of Phosphates (OCP S.A.), owned by the kingdom of Morocco . Both the DMSs rely on complementary models of the SC, used to simulate its activities dynamically. In this context, management is focusing i) on the tactical decisions to negotiate the terms of new agreements (limited number of customers) and so maximize the margin generated by the SC and ii) on the operational decisions to fulfill its obligations under the current agreements while keeping costs down. This paper focuses mainly on the operational management aspect. Highlighting the consequences in terms of time and space of the contemplated operational decisions is largely achieved through the simulation tool, which of course does not preclude recourse to complementary approaches (optimization…) to identify the best course of action. Ex ante assessment of the decisions should be complemented by an ex post assessment by management control, through a tailored management accounting scheme to make a proper economic analysis of the decisions. In the context of production to orders, the management control referential cannot be efficient if it only refers to legacy data. Indeed, the use of simulation techniques is needed in order to obtain a truly relevant referential, one that is built dynamically. We start by delimiting the context of this work ( § 2), and then consider ( § 3) the key concept of routing in order to present ( § 3) some principles of collecting and using the gathered data that we will illustrate ( § 4) with applications in the OCP context before making any conclusion.

2

Research context

Any modeling / simulation (M / S) research on production systems is determined by the objectives sought and by the general characteristics of the system. We shall therefore begin ( §2.1) with a description of the objectives of the research as they determine the choice of relevant information to be gathered and the level at which the model is to be designed. ( §2.2) analyses the information gathering approaches proposed in extent literature showing their limits for the purposes of this research.

Objectives of the "dual" modeling

The Figure 1 summarizes our chosen approach. The combined gathering of field information by SC management experts and management control / management accounting players should make for two consistent and complementary representations of the SC's activities. The basic inputs are technical documents used in the field, complemented by observation, particularly of decision-making practices, where the required information is not set out in writing. Such basic inputs (which are not available in the public domain (and therefore not listed in the bibliography)) are processed in order to design a dual model of SC activities, with an adequate granularity for the DMS to be designed. The desired model is intended for use by a discrete event simulator, which is a relevant technical solution for our purpose. The primary data gathering process and its processing in order to build the foundations of a simulation model poses a number of difficult methodological problems.

Fig. 1 Complementarity and use of Operational Management & Management Control Models

The M / S created for the operational DMS does not call for a fine detail of SC process mapping; on the other hand, it presupposes a good understanding of the main levers available to decision-makers and a proper modeling of the domino effect of consequences of these decisions in time and space. The first step, therefore, consists in an accurate plotting of the concerned physical activities. In order to further inform the decision-making process, beyond the anticipation of consequences of alternative decisions, one needs to measure their economic impact. This implies recourse to a management accounting scheme based on the second M / S. The M / S created for the Management Control DMS stems from a detailed mapping of the productive entities of the SC, using a rather local focus. This should enable a better assessment of cost factors and therefore the design of a relevant management accounting scheme, for use both for decision-making purposes to assess the economic aspects and for subsequent control purposes.

The economic assessment aspect is not the focus of this paper which will only implicitly refer to costs drivers. It is to be used at a later stage in the operational management DMS to fine tune operational decisions and for tactical decision-making purposes. Moreover, the fact of being able to produce to order should drive the development of a dynamic referential for use by the Management Control DMS.

BPM, Supply Chain Costing and Supply Chain Management

In 1980's and '90s, a number of technical and managerial innovations took place simultaneously, along with sweeping economic environment changes that led to root and branch changes in the organization and management of Western businesses. These gradually shifted the traditional approach to functional line management and process reengineering" [START_REF] Hammer | Le Reeingineering: Réinventer l'entreprise pour une amélioration spectaculaire de ses performances[END_REF], activity costing, project management [START_REF] Giard | Pilotages de projet et entreprises[END_REF], management software packages were all managerial and technological breakthroughs stemming from a process approach of organization and the associated software. Accordingly, there was a perceived need to systematically draw up models for almost every aspect of the organization so as to identify the good practices and to organize the acquisition of information concerning the organizational processes. A number of authors and actors have defined [START_REF] Weske | Advances in business process management[END_REF] the Business Process Management (BPM) as one which enables the modeling of the business process. Using collected information about the activities of a complex system such as a SC [START_REF] Hult | Information processing, knowledge development, and strategic supply chain performance[END_REF], a representation of the organizational processes is designed in the form of a knowledge model (KM) of this system. The KM is defined as the translation in natural or graphic language of the structure of the system's activities. A number of authors [START_REF] Raghu | A business process context for Knowledge Management[END_REF] suggest a definition of the system process' KM as the aggregation of information and data used to plot interactions, collaborations and associations between system entities in a workflow form. Concretely, the BPM is made up of three phases [START_REF] Weske | Advances in business process management[END_REF]; [START_REF] Van Der Aalst | Business process management: A survey[END_REF]; [START_REF] Seshasai | An integrated and collaborative framework for business design: A knowledge engineering approach[END_REF]. The first phase has to do with acquisition and validation of the knowledge concerning the organizational process; this phase, whose steps will be described below, is common to knowledge management. The second phase is about formalizing knowledge (using concepts, tools and methods) which is presented as a Business Process Model(our paper deals mainly with this phase).The third phase is that of analysis and of use of the formal models developed in the previous phase [START_REF] Gartner | Application Development and Maintenance Research Note M-16-8153, The BPA Market Cathes another Major Updraft[END_REF]. During the analytical phase, corporate actors analyze, use and expand the KM. Four steps have been identified for knowledge acquisition through partial analysis of extent literature: (i) the first phase is about the choice of knowledge acquisition mode; the choice of method is bound up with the system and with available information. Moreover, a number of approaches may be used simultaneously; (ii) the second phase is about translating the knowledge acquired in the form of rough basic documentation in digital format ; it is key [START_REF] Seshasai | An integrated and collaborative framework for business design: A knowledge engineering approach[END_REF] to store the information in digital format so as to improve productivity and traceability; (iii) the third phase serves to validate the rough translation of the collected information; (iv)the fourth phase concerns the development of basic documentary knowledge to enable the subsequent formalization of the system's organizational process. Note some authors consider this basic documentary knowledge, often presented in natural language, as a model in itself of the corporate processes [START_REF] Scheer | ARIS -Des processus de gestion au système intégré d'applications[END_REF]. Using an iterative approach, basic process knowledge is then expanded as the process is started all over again from phase 1 [12]. Research [12] on corporate use of structured and formalized basic process knowledge highlighted the five following applications (figure 2): (i) the knowledge model is used to design the Information System (data storage, basic data, ERP), [START_REF] Scheer | ARIS -Des processus de gestion au système intégré d'applications[END_REF]; (ii) the knowledge model is used to design decision-making applications (Advanced Planning and Scheduling, optimization models, simulation models) [START_REF] Grigoria | Business Process Intelligence[END_REF] ; (iii) the knowledge model is used to design the performance assessment system (Management Control systems as part of SC Costing), [START_REF] Davies | How do practitioners use conceptual modeling in practice ?[END_REF]15]; (iv) the knowledge model is used to design and validate the current or future corporate organi-zational process through interaction with target system players [START_REF] Hammer | Le Reeingineering: Réinventer l'entreprise pour une amélioration spectaculaire de ses performances[END_REF]; (v) the knowledge model is used for organizational process certification purposes under the quality management approach.

Fig. 2 Multiple uses of knowledge model systems.

Research by [START_REF] Davies | How do practitioners use conceptual modeling in practice ?[END_REF] showed that a given model may be used by different users; one may suppose that the productivity of the formalization process would be greater if it were centralized and performed once and for all, since the knowledge model draws on the same basic knowledge regardless of use. Indeed, this single process mapping performed as part of the modeling exercise of a complex system may be used, for our purposes, indifferently to design the information system, the decision-making rules and the process valuation/optimization system [START_REF] Raghu | A business process context for Knowledge Management[END_REF]. In light of SC complexity, introducing a BPM approach serves to formalize the logistical process between and within the systems making up the SC [12] and serves as a pre-requisite for operational collaboration in the long run. As shown in figure 2, BPM activity, which consists in formalizing process system knowledge, also involves producing a documented model useful for different purposes. Nevertheless, in light of our objectives of design of SC Management decisionmaking support applications, we will focus on use of the knowledge model geared to the routing concept of an SC, and to the creation of a DMS integrating economic metrics.

Knowledge use: routing based modeling of SC processes

The gathering of the technical information yields multiple items of different forms and formats, from which one has to extract the relevant information for modeling/simulation purposes. Methodological considerations lead to a detailed analysis of the notion of routing ( §3.1) and to to generate the relevant information from the detailed information gathered (provided one relies on properly defined aggregation rules (see §3.2)). One must also achieve the relevant level of detail by keeping the number of objects created in the model down to a minimum ( §3.3).

Routing Components and routing breakdown

Routing is central to technical information. Generally speaking, production routing is defined by use of one or several products matching the required characteristics, combined in predetermined quantities, to obtain, after a certain time (processing time), with the help of multiple material (equipment, machinery…) and human resources (operators), all being viewed as components of a processor, the desired product (or products in the case of linked productions).

Figure 3 shows the components of a Routing and their « combination ». To every reference i of an input is associated a bill of materials coefficient q i ; symmetrically, to every reference j of an output is associated the quantity q j produced by the operations. These quantitative data (q i and q j ) are structurally consistent.

Fig. 3. Representation of a Routing

The above general definition helps to breakdown production operations into the different elementary steps, each characterized by an elementary routing. This is referred to as a detailed routing. These elementary steps are connected by logical relationships of precedence (a downstream step may not start until the upstream step has been completed), in which a product made upon completion of an elementary upstream step is used by the next elementary step downstream. These different routings are generated to satisfy different needs (real time order, ordering, scheduling). Detailed routings may be viewed as a description of the production process. Detailed routings gathered in the field generally do not match the required level of detail for a dual modeling/simulation of the SC under review. They, however, enable one to generate the relevant information from the detailed information gathered, provided one relies on properly defined aggregation rules (see §3.2). One must also achieve, in the required model, the relevant level of detail by keeping the number of objects created in the model down to a minimum ( §3.3).

Aggregation Rules

Aggregated activities encompass all of the elementary steps of the detailed routing, together with the products exchanged between these elementary steps. Four rules are relevant to the elementary routing aggregation: (i) The rule of legacy as to time sequence: The time sequence relationship linking the different elementary steps that are merged into an aggregated activity will disappear, as does any trace of the products exchanged between these elementary steps. The aggregated activity inherits the time sequence relationship linking an elementary step to another lying upstream or downstream, but that are not included in the aggregated activity (figure 4). (2) adaptation to line production is straightforward if one considers that the line production process can be approximated by a discrete process handling small batches (for example, a batch corresponding to product volume manufactured in k minutes by the processor, k being the number of minutes).

(3) The duration of aggregated activity is only valid provided there is no interruption in supplies, preventing an elementary activity on the critical path from being performed

(iii) The rules of resource consolidation:

The resources mobilized by every elementary activity are all mobilized by the aggregated activity. Application of this principle in project management poses a problem as it is obvious that the mobilization of a non-storable resource by an aggregated activity does not imply its use throughout the activity. In the context of modeling/simulation of a production process, this objection should be dropped if the proposal described above to allow the process to handle simultaneously n batches is adopted as, at any time, all the non-storable resources are simultaneously consumed by the n batches.

(iv) The flow conservation rules:

The aggregation method should respect the principle of flow conservation: at cruising speed, what enters the plant (expressed in weight or otherwise…) is necessarily equal to what goes out, knowing that some output may be waste.

Definition of the granularity level

The risk of modeling is that of adopting too fine a level of detail. Two principles should guide this effort: define a model that is relevant for the decisions to be taken (i) and limit the number of model components to a minimum (ii).

(i) Modeling relevant for the decisions to be taken:

The level of detail of each of the two M / S should be consistent with the objective of the DMS using it and enable the exchange of relevant information between the two DMSs. Note the issue of a possible decoupling between certain SC sub-systems which serves to circumscribe in time and space the scope of analysis of the consequences of certain decisions. The economic aspect will be looked at subsequently with reference to the management accounting scheme, which is linked to the second DMS. Its aim is to globally minimize overall costs. The tactical management goal of the first DMS is to maximize the margin generated by the new orders, through a contribution to the negotiation process, and, in particular through provisional production capacity, possibly subject to availability of certain raw materials. This corresponds to a wider scope and different missions which may call for the mustering of other approaches, such as mathematical scheduling, to complement the simulation approach. The level of M / S detail for management control purposes is clearly different than that geared to operational management. The complementarity of the two DMSs implies that the basic production unit used for modeling is not shared by other units of the model on which the operational management DMS is based.

(ii) Limitation of the number of components consumed in the modeling:

To facilitate comprehension and maintenance, the proposed model should be as dense as possible (for a required level of detail). The M/S applications enable the design of components from basic components (processors, inventory…), which may be used as new basic components to be reused to build new components. M/S applications also enable use of parameterized routings that may be used in a particular productive sub-system to describe its use by different types of production. Finally, these enable pinpointing a single processor to describe multiple identical processors working side by side. These different possibilities shall be leveraged, taking into account the different aggregation rules proposed.

Examples of application of these principles in the formalization of the gathered data

We present below the application of the principles developed in our research with examples of information gathering and processing. Figure 5 describes the configuration of OCP S.A.'s SC and offers a representation of the information gathered, processed and formalized. The primary information is made up of textual descriptions of the process and its resources, but excludes part of the implicit routing information. A flowchart with a list of additional required information is obtained. The system processes three types of flow; a zoom is proposed on one of these. The granularity level presented here is for information purposes.

Pipeline

Washing documentation highlighted differences related to the type of ore transformed, in terms of system and resources used as well as flow path. The first phase of translation of this data was the creation of a detailed routing for each type of ore input, with the output ("wash concentrate", as it is called) being always the same. Figure 6 represents one of the 4 detailed routings. It features rate and average processing time. The principle of flow conservation is respected. The average processing time is approximately of 26.1; the fact that the process is a cycle complicates the calculation somewhat (the result was obtained by simulation). Figure 7 illustrates the aggregated routing derived from the detailed routing. It should be highlighted that this information is valid in cruising speed and that this is also true for the following examples. A juxtaposition of the 4 detailed routings yields figure 6, which shows a parameterized routing model. The numbered arcs of table 1 serve to identify the rate information (for example, line C 2 corresponds to information of figure 6; the possible neutralization of an arc is noted by a dash. Super components may be designed through recursive construction, thus appearing as a specific category of components. On the Jorf platform, OCP S.A. owns three workshops organized as a flow shop (figure 8). The phosphoric acid and fertilizers production workshops are each represented by a component obtained through the same creation process as that used to build the sulfuric workshop component. The sulfuric and phosphoric acid productions are shown as external inventory as they may be used indifferently by the OCP S.A.'s workshops and those of Jorf's Joint Venture. The super-component is represented synthetically as in figure 9. Jorf's JVs are characterized by production units that are derived from OCP S.A.'s. They may be "grafted" onto the sulfuric acid supply, (which they do not produce) or onto the phosphoric acid supply, in which case, they only manufacture fertilizers, or onto both. The Jorf platform, therefore, is made up of the OCP S.A. production plant onto which the JV's production plants are grafted.

Conclusion

This paper proposes a routing-based modeling approach to a complex logistics process. This approach forms part of a BPM but goes beyond it as the knowledge gathered may be used in different ways (both for management control and operational management purposes through a combination of the physical flows, see fig 2). It therefore stands out as an innovative approach with multiple scientific and management implications. Though its relevance is clearly limited to SCs of the type under review (where DMS may be modeled on activities that are interconnected and where a single totally integrated organization exercises control), our proposed approach appears promising for a wide variety of applications: coupled modeling of "operational levels" should yield decision-making applications including physical and financial aspects; construction of a single referential to measure logistics performance of operations throughout the production process; the construction of real time activity valuation scheme feed into industrial management control referential. In short, there are multiple prospects for implementation of our model.

Bibliography

1

 1

Fig 4 .( 1 )

 41 Fig 4. Rule of time sequence relationship legacy(ii) The rules of consolidation duration:The above analogy with project management helps define the duration of aggregated activity as equal to the duration of the critical path calculated on the flowchart of the detailed routing, where cycles are not noted. This duration consolidation rule is subject to the following three constraints:(1) In discrete production, the processor which performs an activity handles a single batch (or unit) at a time and only processes the next one once the first has been completed. A transposition of this principle to aggregated activity distorts the representation of reality, since the processor performing the first elementary activity of the aggregated activity is in a position to handle a new batch as soon as it has finished the previous batch, without having to wait for the batch it has processed to leave the processor performing the last elementary activity of the aggregated activity.

Fig 5 .

 5 Fig 5. Macro modeling of OCP S.A.'s Supply chainThe process documentation of an ore washing chain (text, tables, maps) supplied was quite exhaustive and we noted that the washing site comprises six identical washing chains. The

  Figures 6..9

9

 9 Figures 6..9

Figures

  Figures 10..14

14

 14 Figures 10..14

Fig 6 .Fig 7 .

 67 Fig 6. Exhaustive and parameterized routing -C 2 ore washing

Fig 8 . 9 .

 89 Fig 8. Example of recursive modeling Fig 9. Example of super-component This plug and play type configuration leads to the model described in figure10, where the Indian JV (IMACID) (producing phosphoric acid), the Brazilian JV (BUNGE) (producing phosphoric acid and fertilizers) and a JV project under study are integrated, thus illustrating the modularity of the approach. In terms of modeling, it suffices to parameterize the OCP S.A.

Fig 10 .

 10 Fig 10. Plug and play configuration

Table 1 :

 1

Rates (tons/hour) of the parameterized routing of figure

6

.

It is made up of a complete industrial sector (described in figure5) from ore extraction (more than half of world reserves belong to OCP S.A.), to production of phosphoric acid and fertilizers. The Jorf site located at the end of this SC is characterized by its production plants, owned by OCP as well as by a number of technically similar plants, jointly managed by OCP and its foreign partners under joint ventures (JV). Moreover, the adjunction of 300 km of pipeline (for minerals transfer) will entirely change the SC to enable implementation of production to orders.