José Telhada’s research while affiliated with University of Minho and other places

Process quality planning should establish the incoming quality inspection plan to achieve the desired quality level with minimum Cost of Quality (CoQ). Additionally, the selection of alternative suppliers must be defined, and, in a dynamic context, the best solution may vary. The purpose of this study is to, through a simulation approach, minimize the total CoQ of two related decisions: i) supplier selection and ii) incoming quality inspection selection. We will determine the CoQ of alternative suppliers and determine the CoQ of alternative incoming inspections that are associated with such decisions. The inputs to the model are components costs, inspection costs, proportion of defectives from incoming lots, Type I and Type II inspection errors, alternative control methods, and the cost of delivering defective components to the manufacturing system. The uncertainty of some inputs is modelled through probability distributions and the dynamic context is modelled through different scenarios. The results from simulations estimate the total CoQ of each alternative decision. This model allows to determine the CoQ of the alternative scenarios and to define a best supplier and incoming quality inspection plan. A numerical example based on a manufacturing process demonstrates the applicability of this model and the results indicate that the optimal solution may vary when the model parameters are updated.

This project is the result of a volunteer program that took place in the Republic Guinea-Bissau (RGB) at the Paediatric Hospital. The Paediatric Hospital was working with the same technologic skills as Portugal in the 70’s years. There was no wired network between departments, no informatic system and all work was handmade. The physicians received incomplete clinical reports and, sometimes, with gross errors. There was no triage neither outpatient short list during the medical urgency period. The outpatients needed to wait for long time to get the analytical report and most time without meal or single bread. On the Clinical Analysis Laboratory, the biologic sample identification and the manual data report were lower changes to be credible and there was no final checklist. This paper describes the improvements made by the authors in the hospital logistical processes and in the development and implementation of an information system that was started in March 2018. These improvements were developed based on lean manufacturing principles, on methods and best practices for some referenced case studies fromAmerica, Saudi Arabia, Italy and England. As a result, the hospital reduced outpatient waiting time, improved Hospital, Laboratory and outpatient outcomes, increased confidence work for physicians and laboratory technics

In material requirements planning (MRP) systems, safety stock and safety time are two well-known inventory buffering strategies to protect against supply and demand uncertainties. While the role of safety stocks in coping with uncertainty is well studied, safety time has received only scarce attention in the supply chain management literature. Particularly, most previous operations research models have typically considered the use of such inventory buffers in a separate fashion, but not together. Here, we propose a decision support system (DSS) to address the problem of integrating optimal safety stock and safety time decisions at the component level, in multi-supplier multi-item single-stage industrial supply chains under dynamic demands and stochastic lead times. The DSS is based on a hybrid bi-objective optimization approach that simultaneously optimizes upstream inventory holding costs and β-service levels, suggesting multiple non-dominated Pareto-optimal solutions to decision-makers. We further explore a weighted closed-form analytical expression to select a single Pareto-optimal point from a set of non-dominated solutions, thereby enhancing the practical application of the proposed DSS. We describe the implementation of our approach in a major automotive electronics company operating under a myriad of components with dynamic demand, uncertain supply and requirements plans with different degrees of sparsity. We show the potential of our approach to improve β-service levels while minimizing inventory-related costs. The results suggest that, in certain cases, it appears to be more cost-effective to combine safety stock with safety time compared to considering each inventory buffer independently.

As maintenance and operation costs increase with usage over time, equipment is replaced when the value of new equipment is more attractive. Some methods have been developed to solve this problem. In the public transport sector, such problems are frequently analyzed by fleet managers and determined by bus age restriction regulations. We propose an Integer Programming model that integrates both budgetary and environmental constraints (CO2 emissions) which, as far as we know, have not previously been studied in conjunction. The study aims to determine the optimal replacement plan for a fleet of diesel buses of different size, age, maintenance costs and emissions rates, with new (less polluting) diesel buses over a time horizon of 50 years. The results indicate that it is possible to reduce emissions with a low annual budget using an optimal replacement policy.

The distribution of goods in urban areas is a major challenge for managers in the public and private sectors, due to population growth, high density in large urban centers and, in many cases, lack of planning in urban cargo transport systems. In this context, the objective of this paper is to propose a novel collaborative urban cargo distribution system for logistics service providers, based on a transshipment terminal and usage of electric cargo bikes, highlighting the main aspects to consider on estimating its beneficial economic and environmental impacts in terms of emissions and the risk factors of the investment. The evaluation of this solution may be based on applying simple vehicle routing heuristics for assessing the distance travelled, costs and emissions. Also, a more sophisticated cost model is proposed to estimate the economic viability and risks associated to the use of electric cargo bikes. Finally, risk aspects can be evaluated through a structured methodology including both qualitative and quantitative approaches.

This paper presents a multiobjective optimization model to find efficient bus fleet combinations taking into account greenhouse gas emissions, conventional air pollutant emissions and costs. The goal is to minimize, simultaneously, three objective functions, Z1 (CO2 emissions), Z2 (Other Types of Emissions), and Z3 (total costs), for a buses fleet of a transit agency. For this case, there were four types of buses (diesel, electric bus, electric bus of fast charging, and CNG (compressed natural gas bus), which were analyzed in three different lines (South-North, Itinga, and South-Central) in Joinville city, Brazil. The respective data were modeled and optimized using MS Excel. Two different scalarization methods (the Weighted Tchebycheff and the Augmented Weighted Tchebycheff) are used for solving this buses fleet management problem. Different tradeoffs, in terms of the objectives, were obtained. The choice of a bus type is directly related to the characteristics (number of stops, average speed among others) of each line. The electrical bus is the best choice for reducing emissions but has a high initial cost and low autonomy. The results indicate that in the South–North line due to the large number of stops and low average speed, the electric bus is the type of dominant. In the other lines, the dominant ones were the diesel bus in the Itinga line and the CNG bus in the South line.

One of the major obstacles for cities to achieve sustainability is the problems related to urban freight transport. Freight transport operations in urban areas are usually carried out by private companies (freight operators and carriers), using public infrastructure, governed by regulations and implemented and monitored by public authorities. In most cases, because there is no prior consultation with the other stakeholders involved in freight transportation, the negative impacts generated from the urban freight distribution are compromised by the implementation of these actions. There is a lack in the literature a decision support system an appropriate that be able to potentialize the involvement between public and private sector of urban freight. This paper look for new ways of responding to these questions. In this context, the objective of this work is to present a methodology based on the application of Concurrent Engineering (CE) principles in design of an Integrated Participative Planning Management System to Support for Urban Freight Distribution (MISPPUFD) - be able to influence and promote behavioral / engagement change to a requirement for greater interaction between policy makers and stakeholders in support of the group decision-making process with regards to urban freight distribution issues. This suggests the importance of a system that promotes interaction and dialogue - through public consultation to better understand the issues and objectives of different stakeholders in the cargo sector, including academic experts and citizens in that partnership. This approach should result in helping policy makers and stakeholders to deal with different complex objectives and decisions and guide the process of participation

The urban distribution of goods is a function of the economic needs of cities, whether imposed by industries, or by commercial establishments and by their inhabitants. This type of transport has become more critical, with the growth of urbanization, which has negative impacts on the environmental, social and economic elements. One of the possible solutions that allow the reduction of air pollutants, noise and congestion, improving the quality of life without compromising the economic development of the city: the replacement of fossil fuel-diesel vans by using electric cargo tricycles. The implementations of solutions based on these alternatives for freight transport in urban areas is far behind in the actual needs. A case study was developed in a company in the segment of courier, express and parcel delivery (CEP) located in the city of São Paulo, Brazil. Required data for the study has been obtained from company sources or collected through direct observation and empirical data. From the experience observed in the field, it was perceived that there is, in fact, little knowledge of the economic benefits that the implementation of new technology transport means and alternative distribution strategies can provide. The results show that replacing diesel vans by electric cargo tricycles along with adequately new distribution strategies can represent savings of up to 31% in operating costs and at least 97% in CO2eq emissions per year. We conclude that it is environmentally friendly and economically viable to eliminate negative externalities in the goods distribution system in urban areas.

The distribution of goods in urban areas is a major challenge for managers in the public and private sectors, due to population growth with large population concentration in large urban centers and, in many cases, lack of planning in urban cargo transport system. In this context, the objective of this study is to present the results of a systematic review of the literature that summarizes the existing research and identify the potential of the use of Urban Centre Consolidation (UCC) with the support of the cargocyclos as a way to mitigate the environmental impact making the urban distribution of goods more sustainable and viable. The paper also presents data from the field research in a case study carried out at a transportation company located in the city of São Paulo.