Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line

Maintenance and production are frequently managed as separate activities although they do interact. Disruptive events such as machine failures may find the company unready to repair the machine immediately leading to time waste. Preventive Maintenance may be carried out and maintenance time reduced to the effective task duration, in order to prevent time waste. Companies and researchers have been focusing on policies able to mitigate the impact of Preventive Maintenance on system availability, by exploiting the knowledge about degradation profiles in machines and the joint information from the machine state and the buffer level. In this work, the mathematical proof of the optimal threshold-based control policy for Preventive Maintenance with inventory cost, maintenance cost, backlog cost is provided. The control policy is defined in terms of buffer thresholds and dependency of the thresholds on the degradation condition. The optimal control policy is proved to include a combination of switching points and hedging points, where the first ones activate the Preventive Maintenance for a given condition and the latter ones control the production rate in order to minimize the surplus. An extensive experimental campaign analyzes the impact of system parameters such as the Maintenance duration on the cost function. The results show that there exists cases in which the optimal policy is dominated by the effect of the hedging points or the switching points, alternatively. Therefore, the proposed method is used to provide suggestions to the management for operative decisions, in order to choose the policy fitting best the system

Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation

The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example

Performance evaluation of multi-stage manufacturing systems operating under feedback and feedforward quality control loops

In manufacturing, the essential product characteristics are often created through multiple stages. Coupling product data obtained through inspection and controllers based on decision models with prediction capabilities enables quality control loops, enhancing both feedback and feedforward mechanisms. This paper proposes a methodology to merge the formulation of feedback and feedforward quality control loops into a performance evaluation model for multi-stage manufacturing systems. This approach evaluates quality control loop impacts system-wide, aiding in configuring and reconfiguring quality gates. A case study illustrates how allocating inspection technologies and efficient decision models improves overall system performance through effective feedback and feedforward control loops

Recent advances in modelling and simulation of surface integrity in machining - A review

Machining is one of the final steps in the manufacturing value chain, where the dimensional tolerances are fine-tuned, and the functional surfaces are generated. Many factors such as the process type, cutting parameters, tool geometry and wear can influence the surface integrity (SI) in machining. Being able to predict and monitor the influence of different parameters on surface integrity provides an opportunity to produce surfaces with predetermined properties. This paper presents an overview of the recent advances in computational and artificial intelligence methods for modelling and simulation of surface integrity in machining and the future research and development trends are highlighted

Part Variation Modeling to Avoid Scrap Parts in Multi-stage Production Systems

Manufacturing systems for today's products are complex systems requiring a variety of different processes in order to be able to manufacture all necessary part features. This also applies to the production of rotating components, which have experienced increasing demand at the latest due to the growth in mobility. As in almost every manufacturing process, quality-reducing defects can occur due to deviations for example tool wear, which cannot always be avoided. Those, that have accumulated from previous process steps can cause the occurrence of superimposed defects. This leads to complex relationships between quality defects in the end product and the numerous parameters of the manufacturing processes. To remain competitive, production must be optimized in order to identify defects as early as possible, as well as their dependencies and variation patterns. The paper presents an approach to identify and model part variations within multi-stage production systems. Subsequently, based on a detected deviation, a downstream compensation strategy can be proposed at an early stage of the manufacturing process, which uses the capability of the overall system to fundamentally eliminate rejects

Long-term proactive management of psoriasis with calcipotriol and betamethasone dipropionate foam: an Italian consensus through a combined nominal group technique and Delphi approach

Background: Although long-term management of psoriasis is paramount, this approach is challenging in clinical practice. In the recent PSO-LONG trial, a fixed-dose combination of betamethasone dipropionate (BD) and calcipotriol (Cal) foam applied twice a week on non-consecutive days for 52 weeks (proactive treatment) reduced the risk of relapse. However, the role of Cal/BD foam in the long-term management of psoriasis needs further clarifications. The ProActive Management (PAM) program, a nationwide Italian project, aims at reaching a consensus on the role of proactive management of psoriasis. Methods: A steering committee generated some statements through the nominal group technique (NGT). The statements were voted by an expert panel in an adapted Delphi voting process. Results: Eighteen statements were proposed, and the majority of them (14/18) reached a consensus during the Delphi voting. The need to provide long-term proactive topical treatment to reduce the risk of relapse for the treatment of challenging diseases sites or in patients where phototherapy or systemic therapies are contraindicated/ineffective was widely recognized. A consensus was reached about the possibility to associate the proactive treatment with systemic and biological therapies, without the need for dose intensification, thus favoring a prolonged remission. Moreover, the proactive treatment was recognized as more effective than weekend therapy in increasing time free from relapses. Approaches to improve adherence, on the other hand, need further investigation. Conclusions: The inclusion in guidelines of a proactive strategy among the effective treatment options will be a fundamental step in the evolution of a mild-moderate psoriasis therapeutic approach

Breast cancer "tailored follow-up" in Italian oncology units: a web-based survey

urpose: Breast cancer follow-up procedures after primary treatment are still a controversial issue. Aim of this study was to investigate, through a web-based survey, surveillance methodologies selected by Italian oncologists in everyday clinical practice. Methods: Referents of Italian medical oncology units were invited to participate to the study via e-mail through the SurveyMonkey website. Participants were asked how, in their institution, exams of disease staging and follow-up are planned in asymptomatic women and if surveillance continues beyond the 5th year. Results: Between February and May 2013, 125 out of 233 (53.6%) invited referents of Italian medical oncology units agreed to participate in the survey. Ninety-seven (77.6%) referents state that modalities of breast cancer follow-up are planned according to the risk of disease progression at diagnosis and only 12 (9.6%) oncology units apply the minimal follow-up procedures according to international guidelines. Minimal follow-up is never applied in high risk asymptomatic women. Ninety-eight (78.4%) oncology units continue follow-up in all patients beyond 5 years. Conclusions: Our survey shows that 90.4% of participating Italian oncology units declare they do not apply the minimal breast cancer follow-up procedures after primary treatment in asymptomatic women, as suggested by national and international guidelines. Interestingly, about 80.0% of interviewed referents performs the so called "tailored follow-up", high intensity for high risk, low intensity for low risk patients. There is an urgent need of randomized clinical trials able to determine the effectiveness of risk-based follow-up modalities, their ideal frequency and persistence in time