On the mechanism of three-body adhesive wear in turning

The paper reveals a hypothesis regarding the adhesive mechanism in metal cutting and its mechanical dynamics. One steel grade, 34CrNiMo 6, 285 HB, and one set of coatings on the cutting tool are reviewed. The adhesive mechanism is a transient vibration, including a feedback system limited by the plastic deformation in the chip. The vibration shows as a cluster of waves with stochastic duration in time. It starts up again after a stochastic lapse of silence. The cycle frequency is around 12.5 kHz and the internal excitation is twice that frequency, as the cutting speed and feed are 200 m/min and 0.2 mm, respectively. The adhesive frequency and amplitude are influenced by the cutting speed and the current wear status. The adhesion is monitored by the sound waves emanating from vibrations in the chip, the part still in the workpiece.

A stochastic detailed scheduling model for periodic maintenance of military rotorcraft

Purpose The purpose of this paper is to develop a stochastic detailed schedule for a preventive/scheduled/periodic maintenance program of a military aircraft, specifically a rotorcraft or helicopter. Design/methodology/approach The new model, entitled the military “periodic aviation maintenance stochastic schedule” (PAM-SS), develops a stochastic detailed schedule for a PUMA SA 330SM helicopter for the 50-h periodic inspection, using cyclic operation network (CYCLONE) and Monte Carlo simulation (MCS) techniques. The PAM-SS model identifies the different periodic inspection tasks of the maintenance schedule, allocates the resources required for each task, evaluates a stochastic duration of each inspection task, evaluates the probability of occurrence for each breakdown or repair, develops the CYCLONE model of the stochastic schedule and simulates the model using MCS. Findings The 50-h maintenance stochastic duration follows a normal probability distribution and has a mean value of 323 min and a standard deviation of 23.7 min. Also, the stochastic maintenance schedule lies between 299 and 306 min for a 99 per cent confidence level. Furthermore, except the pilot and the electrical team (approximately 90 per cent idle), all other teams are around 40 per cent idle. A sensitivity analysis is also performed and yielded that the PAM-SS model is not sensitive to the number of technicians in each team; however, it is highly sensitive to the probability of occurrence of the breakdowns/repairs. Practical implications The PAM-SS model is specifically developed for military rotorcrafts, to manage the different resources involved in the detailed planning and scheduling of the periodic/scheduled maintenance, mainly the 50-h inspection. It evaluates the resources utilization (idleness and queue), the stochastic maintenance duration and identifies backlogs and bottlenecks. Originality/value The PAM-SS tackles military aircraft planning and scheduling in a stochastic methodology, considering uncertainties in all inspection task durations and breakdown or repair durations. The PAM-SS, although developed for rotorcrafts can be further developed for any other type of military aircraft or any other scheduled maintenance program interval.

Comparative Study of Pipeline Deliverables using Deterministic and Stochastic Models

This study aim to proffer solution to the factors causing delay is pipeline construction project deliverables, it compared deterministic model (variable with certainty) and stochastic model (variable with uncertainty), with Six (6) planned project schedules of Brownfield Energy Service Limited for pipeline construction. Time assigned to critical activities, identified from a network analysis, with the aid of the Critical Path Method, expected mean time, both deterministic and stochastic duration was calculated. Program Evaluation Review Techniques (PERT), the variance and standard deviation of the critical activities were also calculated. The probability of completion of a project within a given period was gotten with PERT. Comparing the results for deterministic duration 60 days to 79 days, which is 50% compared to 64%. It was concluded that stochastic model is preferable when scheduling and executing pipeline construction projects, because uncertainties are factored into the planning and scheduling process including delays. Delays during execution stage, occurs mainly due to community related issues, equipment failures, change in job scope and work- men antics but not limited to these. This study advocates elimination of causes of delay, especially before and during project execution phase. It also suggested that every project schedule should follow an order of precedents, prerequisite, and management involvement and cooperation at all stages of the project

Airfield Infrastructure Management Using Network-Level Optimization and Stochastic Duration Modeling

This paper proposes a facility-specific modeling approach to plan maintenance and rehabilitation (M&R) activities on a network of airport runway pavement facilities. The objective of the modeling approach is to minimize system M&R cost while recommending M&R activities for each runway pavement facility over a planning horizon. To do so, pavement condition forecast is derived from estimating stochastic duration models which capture the inherent uncertainty and dynamics in pavement deterioration and impacts of exogenous factors. Building on the pavement condition forecast, a network optimization-based M&R planning framework is developed which accounts for the interdependence of M&R activities among facilities as reflected in (1) the requirement for aggregate pavement performance and (2) simultaneous implementation of a major M&R action on connected facilities. The budget constraint is also respected. The M&R planning framework with the stochastic duration model-based pavement condition forecast is applied to Chicago O’Hare International Airport. It is found that the proposed approach leads to much reduced M&R cost compared to the state-of-the-practice which does not consider the interdependence of M&R activities among different pavement facilities. On the other hand, accounting for the simultaneous implementation of a major M&R action on connected facilities would substantially increase M&R cost.