Paolo Renna

Production planning in reconfigurable enterprises and reconfigurable production systems

Reconfigurable enterprises and reconfigurable production systems represent nowadays one of the key responses towards the organisational and manufacturing needs arising in the new era known as mass customization. The paper proposes an Agent Based approach for the production planning activities in reconfigurable enterprises, characterized by complex, articulated and geographically distributed production capacities contended by many product families and composed by reconfigurable production systems that allow quick adjustment of production capacity and functionality consenting to manufacture different products of the same part family.

Coordination policies to support decision making in distributed production planning

Abstract Distributed production networks are considered organizational structures able to match agility and efficiency necessary to compete in the global market. Performances of such organization structures heavily depend on the ability of the network actors of coordinating their activities. The research proposes to model and design coordination problems within production network by using the Multiple Agent Technology. In particular, the paper proposes new strategies for coordinating production-planning activities within production networks. Such models have been developed and tested by using a proper simulation environment developed by using open source code and architecture. The results of the research can be located at two levels: (a) concerning the specific coordination problem addressed, the research provides some insights to make decisions about the choice of coordination approaches to be used in distributed production planning problems; (b) at more strategic level, the paper shows how Agent Technology and discrete event simulation can be used to build up efficient coordination structures for production networks.

Multi-agent based scheduling in manufacturing cells in a dynamic environment

Manufacturing systems need to develop more strongly time-oriented strategies in order to react to the dynamic conditions of the competitive environment. This research concerns the scheduling of cellular manufacturing systems by multi-agent architecture in real time. This research proposes a coordination approach for the multi-agent architecture based on the computation of internal and external indexes of the generic manufacturing cell. The proposed approach has been compared with an approach based on the workload index in order to provide evidence of the improvements. A simulation environment developed in the ARENA® package was used to implement the approaches and evaluate the performance measures. The performance measures investigated are: throughput time, throughput, work in process, machines average utilisation, and tardiness. Several scenarios are considered: from static to very dynamic conditions for internal and external exceptions of the manufacturing system. The simulation results highlight that the performance of the proposed approach outperforms the performance of the benchmark in all conditions.

Design and reconfiguration models for dynamic cellular manufacturing to handle market changes

In today’s competitive environment, customer demand has become increasingly diversified and customised. In order to stay competitive, the manufacturing companies need to adopt models that are able to rapidly adapt to market changes. The reconfigurable manufacturing system emerges from the scientific literature as a relevant manufacturing paradigm to meet changes and uncertainties in a dynamic manufacturing environment. This research proposes a cellular manufacturing system (CMS) with reconfigurable machines to handle the turbulent market conditions. The approach proposed concerns three mathematical models to support the design, reconfiguration and scheduling of the manufacturing system. The three linked models are developed in LINGO® package. The main optimisation model concerns the design of the CMS, considering product demand not deterministic but described by several discrete probability scenarios. Then, an optimisation sub-model has been developed to manage the reconfiguration at fixed periods. An allocation model is used to allocate the jobs to the manufacturing cells. The proposed approach is compared to a model without reconfiguration activities. A further configuration of the models is the possibility of using remainder cells. The simulation results show that the proposed approach is a promising methodology to support the dynamic CMSs with reconfigurable machines.

Reconfiguration: a key to handle exceptions and performance deteriorations in manufacturing operations

During a manufacturing operation, exceptions may occur dynamically and unpredictably. Their occurrence may lead to the degradation of system performance or, in the worst case scenario may interrupt the production process by causing errors in the schedule plan. This paper classifies three families of exceptions: (1) out-of-order events such as machine breakdowns, (2) operational out-of-ordinary events such as rush orders and (3) deteriorations of manufacturing resource performance such as reductions of machines’ utilization. In all cases, in order to maintain an adequate level of system performance, it is necessary to detect exceptions, to diagnose them quickly and to recover them by taking corrective actions to avoid fault propagations. Decisions concerning how to deal with exceptions, i.e. which strategy to implement, depend on the manufacturing environment (dedicated line, flexible system, reconfigurable system or a mix of them) and the advantages arising from using a certain exception handling policy vary from one production system to another. The activity of reconfiguring manufacturing resources has been demonstrated to be a powerful operation strategy to handle machine breakdowns. This paper extends the concept of ‘reconfiguration for exception handling’ to other families of exceptions and proposes reconfiguration for their recovery. The reconfiguration process is handled by an agent-based control system that implements four negotiation processes among manufacturing resource agents.

Job shop scheduling by pheromone approach in a dynamic environment

Job shop scheduling problem is a NP-hard problem; therefore the objective is to create a schedule that satisfies all the constraints while taking as little overall time as possible. The paper concerns the job shop scheduling problem in cellular manufacturing systems; the schedule is created by a pheromone-based approach. The proposed approach is carried out by a Multi-agent Architecture and it is compared with a coordination approach proposed in literature used as a benchmark. A simulation environment developed in ARENA® package was used to implement the approaches and evaluate the performance measures. The performance measures investigated are: throughput time, throughput, Work In Process, machines average utilisation and tardiness. Several scenarios are considered: from static to very dynamic conditions for internal and external exceptions of the manufacturing system. The simulation results highlighted that the performance of the proposed approach are comparable with the benchmark when the customer demand has a high fluctuation and the manufacturing system is less dynamic.

Evaluating service quality dimensions as antecedents to outpatient satisfaction using back propagation neural network

Nowadays the ability to provide outpatient services with exceptional quality is paramount to long-term survival of hospitals, as the revenues from outpatient services are predicted to equal or exceed inpatient revenues in the near future. Identifying the relative weight of different dimensions of healthcare quality service which concur together to determine outpatients satisfaction is very important, as it can help healthcare managers to allocate resources more efficiently and identify managerial actions able to guarantee higher levels of patients’ satisfaction. This study proposes the use of Artificial Neural Network (ANN) as a knowledge discovery technique for identifying the service quality factors that are important to outpatient. An ANN model is developed on data from a panel of outpatients of public healthcare services.

High Level Planning of Reconfigurable Enterprises: a Game Theoretic Approach

Reconfigurable Enterprises (REs) represent production networks made of different and geographically dispersed plants that, in case of unpredictable market changes, can be reconfigured in order to gather a specific production objective. However, REs effectiveness and efficiency depend on the extent to which global performance is obtained. Basically two approaches are available to reach coordination: centralised or decentralised planning tools. In this paper, the authors propose a novel cooperative game theoretical approach for distributed production planning at high level of a RE; the proposed approach has been benchmarked in front of both a distributed one, based on negotiation, and a centralized one.

Decision model to support the SMEs’ decision to participate or leave a collaborative network

Enterprises need to adopt new business paradigms in order to make a rapid response to market changes and improve the competitiveness. The development of information and communication technology allows the support of new business paradigms such as extended enterprises, virtual organisations, regional clusters, etc. The research proposed concerns the study of a dynamic network in which the partners change in short term periods. The model proposed supports the enterprises in the decisions to participate or exit in a network of enterprises. The model is based on the definition of a set of rules that operate with local information to take the decisions. The local information is the output of the collaboration process; this means that the approach proposed integrates the collaboration methodology and the decision model. This environment is related to independent plants that cooperate with reduced information sharing. A simulation environment is developed to test the approach proposed. The simulation results show that the proposed approach is a very promising tool to support the enterprises participation decisions.

Negotiation policies and coalition tools in e-marketplace environment

The e-marketplace in Business To Business applications allows enterprises to make economic transactions in a virtual marketplace. Often Small and Medium Enterprises (SMEs) do not participate to this potential opportunity because of some distrust as: the benefits of e-marketplace participation are not perceived clearly; SMEs doubt that e-marketplace fits the products offered. The possibility to evaluate the real value added by an e-marketplace can be a driving force to adopting e-marketplace for SMEs. The research proposes negotiation policies, customers tactics and coalition tools as a value added services in e-marketplaces. The e-marketplace scenario is a private neutral linear owned by a third part with catalogue based procurement actions. A Multi Agent System methodology is used to implement the architecture of the e-marketplace. Furthermore, the author proposes the use of discrete-event simulation to test the suggested methodologies and to evaluate the economic value of adopting the proposed negotiation and coalition tools in e-marketplaces. The simulations are conducted in a very dynamic environment and a proper statistical analysis is performed. The simulation results show that the proposed methodologies lead to benefits both for suppliers and customers.