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This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

Construction projects operate within a risky environment. It materialises as delays, which must be prevented or mitigated to avoid becoming amplified into late completion. But previous research has largely ignored how structural complexity of the underlying network schedules shapes their resilience.

This research hypothesizes that schedule structure plays a vital role in its ability to absorb or propagate delays. The impact of activity-level local risk factors is represented via activity duration distributions, i.e. probability density functions. The impact of project-level global risk factors is more challenging because they arise via interactions between multiple activities.

Modelling resilience to local and global risk factors can employ a matrix approach. Simulation shows that delay amplification depends on local structure, not global complexity.

Criticality had merely relied upon a single deterministic analysis of a network schedule to categorize activities as having zero or nonzero float from fixed relative duration a dependency structure. Repeated probabilistic analysis with sampled durations gives criticality indices of activities. This research limits itself to network schedules with point-wise relations between activities.

Managers can use this knowledge to develop schedules that protect their expected project duration with a suitable structural complexity.

Contributions to the body of knowledge are as follows: It converts the dependency structure into a reachability matrix and adds a correlation matrix to capture how the predecessor performance may impact its successors. It correlates criticality of activities with structural complexity indices. And it ranks activities objectively by their cruciality, i.e. potential delay propagation.

Major demographic trends are affecting the work schedules of U.S. employees with likely consequences for health and quality-of-life outcomes. These trends include long work hours, at least for some groups of employees, and an increasing proportion of employees in the U.S. and other countries who are working nonstandard work schedules. This chapter contains a review of the empirical literature linking the number of hours worked and the distribution of those hours at the individual and couple level to a variety of outcomes, cross-sectionally and longitudinally. In addition, because the majority of U.S. workers live in dyads (Jacobs & Gerson (2004). The time divide: Work, family and gender inequality. Cambridge, MA: Harvard University Press), major attention is given to the impact of work hours on the employee's spouse as well as on the employee. It is also noted that the relationship between work hours and outcomes might be different among employed single women with children. Data are presented from two new studies conducted by my research team to fill some of the critical knowledge gaps. Finally, I suggest some directions for future research.

The author tests the hypothesis that the effects of evening and night employment on working parents’ work-to-family conflict and life satisfaction depend on the reasons that individuals name for their schedules. Regression models are fitted to data from an original sample of 589 employed US parents. Partnered (married and cohabiting) fathers who work partially in the evening or night experience less work-to-family conflict if they report personal motives, but schedule motivation does not affect work-to-family conflict among partnered or single mothers. Partnered mothers who work primarily in the evening or at night report higher life satisfaction if they do so for personal reasons, but this effect is not found for single mothers or partnered fathers. Specifically seeing their schedules as facilitating family care matters for partnered mothers, but not fathers. Although nonstandard employment schedules have been linked to poor well-being among working parents, this is the first quantitative study to assess the role of worker motivation to the author’s knowledge. The results are suggestive because they are based on a nonprobability sample of modest size. However, they demonstrate the need for future studies of employment scheduling to collect information on worker motivations. Most night workers in the United States do not select their shifts for personal reasons, putting them at risk for work-to-family conflict and reduced life satisfaction. They deserve extra support in exchange for laboring while others sleep or spend time with family.

Flexible scheduling in school libraries is supported by the American Association for School Libraries (AASL) and the Association for Educational Communications and Technology (AECT). Support is based on the constructivist theory of learning and posits increased learning, collaboration, and visitations by classes, small groups, and individuals to the availability of resources during the time of need, yet there is no direct evidence to support flexible scheduling. The quantitative study sought to examine the relationship between media center scheduling on students’ academic achievement, teacher and media specialist collaboration, and class visitation in an elementary school. The researcher utilized an experimental posttest-only control group design. The point-biserial correlation was utilized to identify any relationship between groups who utilized the media center on a fixed versus a flexible schedule and criterion-referenced test scores. No significant relationship was found between scheduling patterns, student achievement, and collaboration. However, the research supported increased number of visitations by classes on a fixed schedule.

Schedule UTP requires that firms disclose to the IRS the uncertain tax positions that comprise the federal portion of the tax reserve disclosed on their financial statements. To investigate whether Schedule UTP has been an effective audit tool to the IRS, we use financial statement disclosures of reductions in reserves due to a lapse in the statute of limitations (Lapse). We find that the probability of a Lapse is 3.4 percent lower after Schedule UTP. However, this result is driven by domestic firms; we do not find evidence that Schedule UTP has been effective in the audit of multinational firms.

This study examines the scheduling problem for a two-stage flowshop. All jobs are immediately available for processing and job characteristics including the processing times and due dates are known and certain. The goals of the scheduling problem are (1) to minimize the total flowtime for all jobs, (2) to minimize the total number of tardy jobs, and (3) to minimize both the total flowtime and the total number of tardy jobs simultaneously. Lower bound performances with respect to the total flowtime and the total number of tardy jobs are presented. Subsequently, this study identifies the special structure of schedules with minimum flowtime and minimum number of tardy jobs and develops three sets of heuristics which generate a Pareto set of bicriteria schedules. For each heuristic procedure, there are four options available for schedule generation. In addition, we provide enhancements to a variety of lower bounds with respect to flowtime and number of tardy jobs in a flowshop environment. Proofs and discussions to lower bound results are also included.