This paper proposes a composite index, called the AR Index, to assess the agility and resilience of automotive companies and their respective supply chains. As a first step, a model to support the AR Index is developed. Next, an AR Index for the automotive supply chain is suggested using a set of relevant Agile and Resilient supply chain practices. The Delphi technique was used to obtain a series of weights for those practices. Finally a case study approach is used to illustrate the application of the AR Index. This study represents an original approach that suggests a unique composite indicator for the Agile and Resilient paradigms in the context of automotive supply chains

The present paper presents a physical prototype that simulates the response of a single degree of freedom dynamic system, equipped with a novel semi-active vibration control device. This device comprises two superelastic NiTi elements working in phase opposition and aims to prevent deck unseating in simply supported bridges, during a seismic excitation. The special design of this device allows to avoid problems related to stress–relaxation phenomena and material degradation because of cyclic loading that have been observed in similar passive dissipation devices. The proposed design uses a strategy that permits the continuous adapting of the accumulated stress in the NiTi wires, on the basis of the response of the device to external excitations. Although unloaded, the NiTi elements remain strain/stress free, preventing stress–relaxation phenomena. With the occurrence of a dynamic excitation, a cumulative strain/stress process in the superelastic wires is initiated, enabling higher martensite transformation ratios and therefore increasing the damping capacities of the system while keeping the stresses in the wires inside a narrower superelastic window. The strain/stress accumulation in the superelastic wires is a direct result of the motion of the structure itself, with no need for external energy input.

This work aimed to study the effect of different pre-treatments applied to a potato peel residue, in a thermophilic Anaerobic Digestion (AD) process. All samples were subjected to a mechanical pre-treatment through milling to a particle size below 2 mm. The thermal pre-treatments applied consisted of autoclaving the residue at a gauge pressure of 1.2 bar, under a temperature of 122°C, and for 20, 35 and 55 minutes: assays E122.20, E122.35 and E122.55, respectively. The control assay was performed on a ground residue, which was not submitted to any thermal pre-treatment. All pre-treated residues were subjected to an AD process in a CSTR reactor at 49±1°C. The experimental data showed that the highest methane percentages were very similar (about 92% v/v) for all samples submitted to the thermal pre-treatments. For the control assay, the highest percentage of methane was 87.9% (v/v). The highest biogas yields were recorded in the trial E122.35 (646±50 cm3.g-1 CODremoved), against only 250±20 cm3.g-1 CODremoved for the control assay. The highest biogas yields for VSremoved were attained in the assays E122.55 and E122.35, with values of 646±48 cm3.g-1 VSremoved and 634±59 cm3.g-1 VSremoved, respectively. Globally, the yields registered for the assay E122.35 were similar to those determined in the assay E122.55. Due to the lower energy consumption during the pre-treatment performed in the assay E122.35, this was considered to be the most suitable pre-treatment for this type of residue.

A rapidly changing market leads to software systems with highly volatile requirements. In many cases, new demands in software can often be met by extending the functionality of systems already in operation. By modularizing volatile requirements that can be altered at the client’s initiative or according to market demands, we can build a stepping-stone for management of requirements change. The volatility must be managed in a way that reduces the time and costs associated with updating a system to meet the new requirements. In this chapter, we present an approach for handling volatile concerns during early life cycle software modeling. The key insight is that techniques for aspect-oriented software development can be applied to modularize volatility and to weave volatile concerns into the base software artifacts.

Purpose - The main objective of this paper is to identify and rank a set of performance measures using the Interpretive Structural Modeling (ISM) approach to support the automotive supply chain performance evaluation.
Design/methodology/approach - The paper develops a framework to analyze the interactions among a suggested set of performance measures using the {ISM} approach. To identify the contextual relationships among the suggested measures, five experts from the automotive industry were consulted.
Findings - Using the {ISM} approach the performance measures were clustered attending to their driving and dependence power. Inventory level and lead time are the two performance measures at the bottom level of the hierarchy, implying higher driving power. Also, operational costs, business wastage, environmental costs, delivery time and customer satisfaction are identified as autonomous measures. This means that they are relatively disconnected from the other suggested performance measures. It is also observed that the cash-to-cash cycle is a weak driver but strongly dependent on the other performance measures.
Practical implications - The proposed approach gives managers a better understanding on mutual influences of performance measures (driving performance measures) and also those measures which are most influenced by others (dependent performance measures). Using {ISM} managers can get insight on the order and direction of complex relations among the suggested performance measures. This kind of information is strategic for managers could identify which performance measures they should concentrate on, and how they can manage the tradeoffs between them.
Originality/value - This paper highlights the deployment of {ISM} as a manager' decision support tool in the identification and ranking of a set of performance measures to make part of a supply chain performance measurement system.

The advancement of CMOS technology led to the integration of more complex functions. In the particular of wireless transceivers, integrated LC tanks are becoming popular both for VCOs and integrated filters [1]. For RF applications the main challenge is still the design of integrated inductors with the maximum quality factor. For that purpose, tapered, i.e., variable width inductors have been proposed in the literature. In this paper, analytical expressions for the determination the pi-model parameters, for the characterization of variable width integrated inductors are proposed. The expressions rely exclusively on geometrical and technological parameters, thus granting the rapid adaptation of the model to different technologies. The results obtained with the model are compared against simulation with ASITIC, showing errors below 10%. The model is then integrated into an optimization procedure where inductors with a quality factor improvement in the order of 20-30% are obtained, when compared with fixed width inductors.