Short-term manpower management in manufacturing systems: new requirements and DSS prototyping

The short-term planning and scheduling of discrete manufacturing systems has mostly focused in the past on the management of machines, implicitly considered as the critical resources of the workshops. Some of the present schedulers claim to also manage human resources, but perform most of the time a local allocation of operators to machines, these operators having regular working hours. However, it seems clear that the workforce has a specificity that should be better taken into account by short-term planning facilities. Moreover, the variability of the weekly working hours through the year will shortly become a rule and not anymore an exception. On the base of a questionnaire answered by 19 French companies of different sizes and industrial sectors, we have tried to identify more precisely some industrial requirements concerning the short-term management of human resources. The growing interest in annualised hours together with the lack of software tools that allow to implement it practically is one of the results of this questionnaire. We suggest in this article the specification of a decision support system for short-term manpower management under annualised hours, taking into account the competence of the operators. A software prototype has been developed according to these specifications; the results of a simple but representative example are described

Scheduling uncertain orders in the customer–subcontractor context

Within the customer–subcontractor negotiation process, the first problem of the subcontractor is to provide the customer with a reliable order lead-time although his workload is partially uncertain. Actually, a part of the subcontractor workload is composed of orders under negotiation which can be either confirmed or cancelled. Fuzzy logic and possibility theory have widely been used in scheduling in order to represent the uncertainty or imprecision of processing times, but the existence of the manufacturing orders is not usually set into question. We suggest a method allowing to take into account the uncertainty of subcontracted orders. This method is consistent with list scheduling: as a consequence, it can be used in many classical schedulers. Its implementation in a scheduler prototype called TAPAS is described. In this article, we focus on the performance of validation tests which show the interest of the method

Ordonnancement interactif basé sur des indicateurs : Applications à la gestion de commandes incertaines et à l'affectation des opérateurs

Pour répondre aux attentes de clients de plus en plus exigeants, les entreprises d'aujourd'hui doivent accroître leur compétitivité, leur productivité et leur réactivité. Pour répondre à ces exigences, la fonction ordonnancement se doit d'être plus réactive, plus performante et plus adaptée aux spécificités des compagnies. Parmi les différentes possibilités d'évolution de l'ordonnancement, la voie de l'ordonnancement interactif semble répondre à ces besoins, et parmi les approches possibles de l'interactivité, l'utilisation d'indicateurs permet au gestionnaire d'atelier de connaître toutes les données nécessaires à la mise au point d'un ordonnancement performant. Quatre types d'indicateurs ont été définis : - des indicateurs de contexte décrivant l'état général de l'atelier, - des indicateurs de diagnostic aidant à identifier les causes de problèmes courants, - des indicateurs d'action renseignant sur la pertinence et l'efficacité de l'utilisation des degrés de liberté, - des indicateurs de performance, évaluant les performances de l'ordonnancement par rapport aux objectifs de l'entreprise. Cette approche de l'ordonnancement interactif a été appliquée à deux problématiques actuelles. Des indicateurs spécifiques à ces deux problèmes ont été définis. La première application concerne la prise en compte dans l'ordonnancement de commandes incertaines, encore en cours de négociation. La deuxième application concerne la gestion des opérateurs de production à court terme, au niveau de l'ordonnancement. Un outil de construction de tableaux de bord mettant en oeuvre ces différents indicateurs a été réalisé dans le cadre d'un projet européen (le projet ASPIRE)

Shared resources scheduling using a multi-agent model: the DSCEP framework

Recently, multi-agent systems have been successfully applied to the scheduling problem. A new multi- agent framework, called DSCEP (distributed, supervisor, customers, environment, producers), is suggested in this paper. This framework is developed base on the subsistent SCEP models, especial for shared resources scheduling activities. It introduces a dialogue between three kinds of evolved SCEP models leading to a high level of co-operation. It provides a more efficient control of the consequences generated by the local decisions than usual systems for each SCEP model. It also provides different algorithms in order to handle the disturbances occurring at different ranks in manufacturing process. As a consequence, the DSCEP framework can be adapted for various scheduling/planning problems. This model is applied to the shared resources scheduling problem of complex systems, and provide a natural cohabitation between infinite capacity scheduling processes, performed by the multi-site manufacturing orders, and finite capacity scheduling processes, performed by local or remote machines

Planification des activités de transport d’une entreprise 3PL par une approche multi-agent

La répartition et l'éloignement des sites de production d'entreprises en réseau, l'éloignement et la multiplicité des centres de distribution ou l'explosion du commerce en ligne ont entrainé une augmentation croissante du nombre de demandes de transport dans le monde. Cette augmentation du volume de transports de biens et de marchandises, ajoutée au nombre croissant de déplacements de passagers a conduit à une augmentation du nombre de moyens de transport (véhicules, avions, bateaux, etc.) avec pour conséquence une augmentation de la capacité des voies de communication arrivées à saturation (autoroutes, lignes aériennes, voies de navigation), un élargissement des zones de stockage (ports, aéroports, entrepôts, etc.) et une augmentation de la pollution impactant durablement l'environnement. Dans ce contexte, l'organisation, la gestion et la planification des transports, devenues cruciales, ont favorisé l'apparition de nombreuses sociétés spécialisées (3PL) proposant une mutualisation des moyens de transport et une gestion centralisée. L'objectif de cet article est de présenter une architecture distribuée de planification des activités de transport visant à mieux utiliser les ressources de transport par le regroupement en fonction du contexte de planification de plusieurs ordres de transport

Collaborative transportation for small and medium enterprises for advancing the emerging countries

International audienceFood needs are growing rapidly with the growing population especially in case of developing countries where food preservation technology is not that much mature or even not available. It results enormous increase in prices of food commodities and higher growth rate of inflation each year. Additionally population is dispersed in the country in form of very small and large cities. Similarly, food grown in the country is also dispersed in the different areas of the country. This is highly necessary to use effective modes of transport, to collect food from these regions and distribute it with equilibrium in all the human living regions. Additionally to reduce the wastage of food in case of food shortage especially in some part of the African continent region. Food products and ingredients found and grown in one region are transported to another region, making it possible to use and eat them where they are not found. Small farmers or food producers to reach the scattered areas to distribute their products at time and cost effectively could not purchase their own vehicles, ships or planes to transport their goods. These companies contact third party transporter companies to transport their products, same as a courier company. These companies are called Third Party Logistics enterprises (3PL). These 3PL enterprises take the responsibility of performing logistics functions entirely or partially of an organization. They manage their own fleet of vehicles which drive in a certain and region. The diversity of clients due to different kind of product distribution (fresh, frozen etc.), distance from production companies and distribution cities, the size of the transport network make it even very complicated for a 3PL transporter to manage transportation planning and make efficient use of their resources. Moreover a single 3PL transporter also covers a limited region; they must collaborate with other 3PL enterprises which operate in other regions to make the delivery of the products to faraway locations. Complexity of transportation planning increases further in case of multiple 3PLE enterprises collaborating for the fulfilment of a transport order(s). The objective of this paper is to present a collaborative and distributed model for transportation planning activities aimed at better utilize transport resources by grouping several orders of transports for each effective displacement

Semantic transportation planning for food products supply chain ecosystem within difficult geographic zones

Purpose – In difficult geographical zones (mountain, intra-cities areas, etc.), many shippers, from small and medium enterprises to individuals, may demand delivery of different food products ( fresh, refrigerated, frozen, etc.) in small quantities. On the other side, carrier companies wish to use their vehicles optimally. Taking into account the perishability constraints (short-shelflife, temperature limits, etc.) of the transported food products and environmentalconstraints (pollution, carbon impact) while consolidatingmultiple kinds of food products to use vehicles optimally is not achieved by current transportation planning solutions. The purpose of this paper is to present an interoperable solution of a marketplace, formed by shippers and carriers, dedicated to the schedule of food transport orders. Design/methodology/approach – This transportation planning system named Interoperable-Pathfinder, Order, Vehicle, Environment and Supervisor (I-POVES) is an interoperable multi-agent system, based on the SCEP (supervisor, customer, environment and producer) model (Archimede and Coudert, 2001). Ontologies are developed to create the planning marketplace comprising demands and offers from different sources (multiple shippers and carriers). Findings – A hierarchy ontology for food products. A transporter system ontology. A global ontology that contains all shared concepts used by local ontologies of both shippers and carriers. I-POVES an interoperable model, which facilitates collaboration between carriers and their shippers through its active agents. Practical implications – I-POVES is tested on a case study from the TECCAS Poctefa project, comprising transport and food companies from both sides of the Pyrenees (France and Spain). Originality/value – There has been much work in the literature on the delivery of products, but very few on the delivery of food products. Work related to delivery of food products focuses mostly on timely delivery for avoiding its wastage. In this paper, constraints related to food products and to environment (pollution and carbon impact) of transport resources are taken into account while planning the delivery

Scheduling of production and maintenance activities using multi-agents system

Manufacturing systems are usually confronted to conflicting situations between production and maintenance ser- vices since their activities are considered as source of disturbance to each other. In order to reduce these conflicts, a multi-agents system SCEMP (Supervisor, Customer, Environment, Maintainer and Producer) is proposed in this paper, making sure that these two entities collaborate in order to achieve a common goal. It consists of scheduling the production activities according to the health states of the machines. The main idea is to use the prediction of the durations of use and remaining useful lifetimes of the machines devices, which can be obtained using prognostic techniques. This enables simultaneous scheduling of production and maintenance activities

An approach for joint scheduling of production and predictive maintenance activities

The Industry 4.0 paradigm, thanks to the deployment of cutting-edge technologies enabling the deployment of new services, contributes to improve the agility of productive organizations. Among these services, the Prognostic and Health Management (PHM) contributes to the health assessment of the manufacturing resources and to prognose their future conditions by providing decision supports for production and predictive maintenance management. However, the future conditions of technical production resources depend on the productive tasks they will have to carry out. If their future conditions will not satisfy production criteria, maintenance tasks will have to be planned and productive tasks will be delayed or assigned to other resources for which their future conditions considering these new tasks must be assessed. In this context, a multi-agent system SCEMP (Supervisor, Customers, Environment, Maintainers and Producers) is here proposed in which production scheduling and predictive maintenance planning collaborate and exploit decision supports provided by PHM modules. The proposed multi-agent system provides a framework in which production and the predictive maintenance activities can be scheduled simultaneously by compromising on their objectives. During the scheduling process, SCEMP enables to identify the needed predictive maintenance from the assignments of production tasks to machines, the machine component prognoses and machine models. It schedules production tasks and predictive maintenance activities according to the number, competencies and availabilities of production and maintenance resources. The SCEMP framework is described and presented in the tough job shop context. For this context, case studies have been generated and scheduled within acceptable computation times. To illustrate the SCEMP functioning, some simplified case studies are detailed with the obtained performances. It is flexible and can be adapted to various manufacturing situations. It can also be used to assess the interest of implementing prognostic functions for machine components

Process for joint scheduling based on health assessment of technical resources

Production and maintenance services are usually in conflict since their activities are performed on the same resources, their operations are often considered as sources of disturbance to each other. The objective of this paper is to describe a process enabling to schedule simultaneously the production activities and maintenance operations. The proposed process is based on a multi-agents system that has shown its effectiveness in dealing with conflict situations. It consists in scheduling the production activities on the resources taking into consideration their health states. Thus, instead of waiting for the resource to fail or of planning in advance preventive maintenances where some would be unneeded, the health assesment functions provide information about the reliability of the production technical resources. Among this information, degradation measurements permit the prediction of the remaining durations of use also known as remaining useful lifetimes. Thus they enable prior planning for maintenance orders and scheduling the production activities, so that conflicts can be managed between maintenance and planning activities