The continuous progress of technology affects all aspects of life and business, dynamically. In order to take the advantaging of technology development, business owners need to adapt themselves with the changes stemming from it. Digitalization of production and service processes is one of the directions that alignment with it will bring many privileges. Internet of Things, cyber-physical system, and artificial intelligence are the popular components of digitalization that constantly undergo evolution. Utilizing these advanced components enables business owners to transform the product-centric processes to smart control digital service-oriented ones. The main motivation of current research work is analysis a theoretical thematic of literature on IoT and CPS servitization topics to shed the light on the main areas that the researchers are focusing on since 2009 and bridge the gap that exists in the literature regarding the implementation of these technologies in the remote monitoring processes in the maritime sector. The result of the literature examination revealed five dominant areas. Through utilizing these disclosed areas, a ten-step approach block diagram for IoT-based 'smart product servitization' was designed. The proposed framework supports companies to take the first steps toward remote monitoring servitization through the implementation of IoT and CPS to produce a fully integrated smart monitor system to improve assets' health and performance and reduce costs and waiting time. Moreover, a case study of a smart injector for marine engine is analysed to propose a working framework supporting the implementation of IoT and CPS to communicate the added-value data within the smart system built on five modules: process control module, process diagnosis module, healing module, storage module, and human interaction module.

Abstract Optimal planning for distribution networks of perishable products is addressed by means of a two‐step approach pursuing both strategic and tactical goals. The distribution network is represented as a directed graph, and discrete‐time dynamic equations are devised to model the storage and transportation of products. The first decision step consists of an optimization problem to account for a strategic viewpoint. In particular, this problem allows to select optimal values for replenishment cycles of products, safety stocks, and amounts of products to be transferred among the nodes of the network by considering uncertainty on long‐term demand predictions. The second decision step requires the solution of rolling‐horizon optimization problems at the various time buckets that exploit accurate, short‐term predictions of customers' demands according to a tactical perspective. In this case, the strategic decisions on the amounts of products to be transferred are tuned according to the available short‐term predictions of demands. The effectiveness of the proposed approach is showcased by simulations in a case study, in comparison with a classical lot‐for‐lot strategy.

The capability of the deflection network to provide circuit service, i.e., virtual circuit service with guaranteed bandwidth, is investigated. Such a capability is achieved by modifying the datagram access algorithm and by introducing additional information in the packet header which allows prioritized access via token requests. This mechanism guarantees the needed resources to the already established connections. A second mechanism, which is superimposed on the previous one, is used to measure the resources available and to assign them upon request. The whole mechanism is completely distributed and very robust, since it is based on measures that reflect the real status of the network. A performance analysis is carried out by simulation. In particular, the capability is shown to guarantee the bandwidth to each connection, and the degradation in the network's maximum throughput due to the token mechanism is investigated. Some modifications to improve the circuit capacity are introduced and their effectiveness is evaluated.>