A Multi-Skilled Approach to Property Maintenance Considering Temporal, Spatial and Resource Constraints

With the continued increase in age of the United States housing and building stock, as well as the continued need to maintain properties across the U.S., the need for timely, cost-optimal maintenance is ever more critical. This paper proposes the application of a mathematical model to aid in the scheduling and assignment of construction and maintenance tasks, considering the multi-skilled workforce. The benefit of this approach is to take advantage of the economies of scale that can be developed using cross-functional skilled workers with varying levels of competence and efficiency. This approach schedules and assigns tasks using data from maintenance task software datasets, using the least-cost, competent worker available for the job while also considering the trade-off between skilled labor cost and travel costs, both in terms of travel wage and vehicle wear and tear. The model is enhanced to include pairing between a mentor and an apprentice, where combined efficiency and pairing costs are considered at the same time as travel costs. Due to the practical nature of this research, a case organization was used and data from that firm was analyzed so that operational insights into the necessity of such a model could be considered. The mathematical backbone of the optimization approach to multi-skilled resource allocation considers the temporal and spatial demands of a geographically dispersed property management program. Actual, as opposed to sample, data allows us to evaluate the real financial implications on the case firm, if such an approach to scheduling is used. The generalization of this data provides excellent fit for a model that can be used to assign the best capable worker to the most cost-efficient task, considering deadlines, priorities and availability. Results of this scheduling approach provide significant cost and resource reductions over the historical firm performance, though practical considerations should temper that expectation. The above approach offers exceptional scalability and adaptability with the continued advancement of algorithm approaches to network-distribution and peer-to-peer work platforms

Robustness in the personnel shift scheduling problem : the modelling and validation of different proactive and reactive strategies

The personnel planning process in any organization aims to ensure that the organization can offer a desired service level to their customers at a minimal personnel cost and maximal personnel satisfaction. This process consists of three hierarchical phases characterized by differing levels of decision freedom and uncertainty about the future personnel demand and availability. In this respect, the personnel planner faces a large and medium level of uncertainty and decision freedom in the strategic staffing phase and the tactical scheduling phase, respectively. In these phases, the personnel planner manages the uncertainty by making assumptions and predictions about the future. Based on these assumptions and predictions, the personnel planner makes decisions about the number of employees to be hired and assigned to work during specific points in time. These decisions constrain the decision freedom in the operational allocation phase, in which the personnel planner obtains the most recent information on the actual personnel demand and availability. This information may differ from the assumptions and predictions, and affect the service level and personnel cost and satisfaction. As such, the moment the personnel planner faces the lowest level of uncertainty, (s)he also has the lowest level of decision freedom. In this respect, this dissertation aims to propose strategies to anticipate and deal with unexpected divergences between the previously established assumptions and predictions, and the actual personnel demand and availability

A MILP model for an integrated project scheduling and multi-skilled workforce allocation with flexible working hours

In this paper, we integrate two decision problems arising in various applications such as production planning and project management: the project scheduling problem, which consists in scheduling a set of precedence-constrained tasks, where each task requires executing a set of skills to be performed, and the workforce allocation problem which includes assigning workers as scarce resources to the skills of each task. These two problems are interrelated as the tasks durations are not predefined, but depend on the number of workers assigned to that task as well as their skill levels. We here present a mixed integer linear programming model that considers important real life aspects related to the flexibility in the use of human resources, such as multi-skilled workers whose skill levels are different and measured by their efficiencies. Hence, execution times of the same workload by different workers vary according to these efficiencies. Moreover, the model considers the flexible working time of employees; i.e. the daily and weekly workload of a given worker may vary from one period to another according to the work required. Furthermore, efficient team building is incorporated in this model; i.e. assigning an expert worker and one or more apprentice worker(s) together with the purpose of skill development thanks to knowledge transfer. A numerical example is provided to check the performance of the model

Applying the principles of spatial modelling to the management of biodiversity in the fragmented landscapes of south-western Australia

Biodiversity conservation throughout the world is challenged by the impacts of a changing climate on fragmented landscapes. To mitigate these threats, conservation managers require models which can demonstrate the consequences of both negative impacts and management actions. This need can be addressed through spatial modelling applications. Unfortunately, throughout much of the world, spatial modelling is forgone, being seen as requiring skills and resources beyond the means of many conservation planners and managers. This thesis seeks to address this dilemma by delivering criteria for a successful modelling application and by providing case studies which demonstrate how appropriate modelling can be undertaken without highly specialised skills or prohibitively expensive software and equipment. In this way it facilitates the delivery of better targeted and, consequently more effective, management actions. For my case studies I have used the south-western corner of Australia as a demonstration landscape. This region is recognised internationally as a “biodiversity hotspot,” not only for the biological richness and uniqueness of species but also for the level of threat to which they are subject. Like many landscapes throughout the world, much or this region’s natural biota exists in fragmented, fragile and degraded patches and is therefore highly vulnerable to the anticipated impacts of anthropogenic global warming. In this thesis I have: 1) examined the principles of spatial modelling and reviewed how spatial modelling has been applied to conservation management in this region, 2) conducted examples of different forms of spatial modelling using actual regional conservation management issues, and 3) demonstrated how these examples can be incorporated into conservation management planning. My key findings are: Spatial modelling provides users with an opportunity to effectively test hypotheses, thereby informing the planning process and improving conservation outcomes. Where spatial modelling is omitted from the process, knowledge gaps are often addressed by the axiomatic and by assumption. This is contrary to the principles of effective adaptive management. Modelling tools are inherently more effective when selected for their capacity to meet a planning objective rather than where projects are tailored to meet a model’s capacity. The coordinated use of multiple tools can often provide a more robust understanding of the consequences impacts and mitigating actions. All tools and data sets used should be utilised with a clear and acknowledged understanding of their suitability, strengths and limitations. A wide range of spatial modelling tools (and data sets) are freely and readily available to conservation managers. Most of these come with excellent tutorials and support services. Data gaps can often be addressed through targeted field observations, obtained through complimentary planning processes, or synthesised from accessible data sets. There is a very large body of peer reviewed literature demonstrating means by which others have applied existing modelling tools, or developed tools themselves, to meet a wide range of applications. Accessing this literature is an excellent means of building spatial modelling capacity. New and improved tools, methodologies and data sets are constantly being developed. A failure to implement effective spatial modelling is becoming increasing difficult to justify

Modeling and Managing Engineering Changes in a Complex Product Development Process

Today\u27s hyper-competitive worldwide market, turbulent environment, demanding customers, and diverse technological advancements force any corporations who develop new products to look into all the possible areas of improvement in the entire product lifecycle management process. One of the areas that both scholars and practitioners have overlooked in the past is Engineering Change Management (ECM). The vision behind this dissertation is to ultimately bridge this gap by identifying main characteristics of a New Product Development (NPD) process that are potentially associated with the occurrence and magnitude of iterations and Engineering Changes (ECs), developing means to quantify these characteristics as well as the interrelationships between them in a computer simulation model, testing the effects of different parameter settings and various coordination policies on project performance, and finally gaining operational insights considering all relevant EC impacts. The causes for four major ECM problems (occurrence of ECs, long EC lead time, high EC cost, and occurrence frequency of iterations and ECs), are first discussed diagrammatically and qualitatively. Factors that contribute to particular system behavior patterns and the causal links between them are identified through the exploratory construction of causal/causal-loop diagrams. To further understand the nature of NPD/ECM problems and verify the key assumptions made in the conceptual causal framework, three field survey studies were conducted in the summer of 2010 and 2011. Information and data were collected to assess the current practice in automobile and information technology industries where EC problems are commonly encountered. ased upon the intuitive understanding gained from these two preparation work, a Discrete Event Simulation (DES) model is proposed. In addition to combining essential project features, such as concurrent engineering, cross functional integration, resource constraints, etc., it is distinct from existing research by introducing the capability of differentiating and characterizing various levels of uncertainties (activity uncertainty, solution uncertainty, and environmental uncertainty) that are dynamically associated with an NPD project and consequently result in stochastic occurrence of NPD iterations and ECs of two different types (emergent ECs and initiated ECs) as the project unfolds. Moreover, feedback-loop relationships among model variables are included in the DES model to enable more accurate prediction of dynamic work flow. Using a numerical example, different project-related model features (e.g., learning curve effects, rework likelihood, and level of dependency of product configuration) and coordination policies (e.g., overlapping strategy, rework review strategy, IEC batching policy, and resource allocation policy) are tested and analyzed in detail concerning three major performance indicators: lead time, cost, and quality, based on which decision-making suggestions regarding EC impacts are drawn from a systems perspective. Simulation results confirm that the nonlinear dynamics of interactions between NPD and ECM plays a vital role in determining the final performance of development efforts

Upland crop technologies in Cambodia: economic evaluations and some adoption issues

Agricultural research and development (R&D) has being conducted in the upland districts of Cambodia to develop new farming systems and crop management technologies. Levels of farm income in these areas are relatively low due to small farm sizes and low crop productivity. Work is also planned to encourage the process of adoption of these technologies, and here we investigate how this process can be facilitated. A literature review identifies two important technology characteristics, ‘relative advantage’ and ‘trialability’, for successful adoption. Minimum or target rates of return on investment in new technologies are discussed as a means of investigating how much improvement in relative advantage might be enough to encourage successful adoption of the technology. A number of economic assessments of new crop methodologies in Cambodian upland districts and farming systems are presented. Some technologies show an encouraging return on investment from the viewpoint of the Cambodian farmer – rhizobium inoculation of soybean seed had an indicated return of up to 600% on the investment depending on the cost to the grower. Other issues are also likely to be important in discussing change to farming systems, for instance social issues in the village/community context. We present a proposal for a participatory learning process in which economic and social issues are highlighted, to encourage adoption of new crop technologies in local Cambodian contexts.New technology, adoption, upland crops, Cambodia, economic assessment, social, Crop Production/Industries, Institutional and Behavioral Economics, Research and Development/Tech Change/Emerging Technologies,

Framework For Quantifying And Tailoring Complexity And Risk To Manage Uncertainty In Developing Complex Products And Systems

In recent years there has been a renewed interest in product complexity due its negative impact on launch performance. Research indicates that underestimating complexity is one of the most common errors repeated by new product development (NPD) teams. It was concluded that companies that successfully manage complexity can maintain a competitive advantage. This is particularly true of CoPS projects (Complex Products and Systems) which are defined as large-scale, high value, engineering intensive products and systems. Investment in CoPS projects continues to grow worldwide, with recent estimates placed at over $500B annually. In this research we present methods to improve the planning and coordination of complexity and risk in CoPS projects to support launch success. The methods are designed to be consistent with systems engineering practices which are commonly used in their development. The research proposes novel methods for the assessment, quantification, and management of development complexity and risk. The models are initiated from preliminary customer requirements so they may be implemented at the earliest point in the development process and yield the most significant cost savings and impact. The models presented are validated on a large-scale defense industry project and experimental case study example. The research demonstrates that development complexity and risk can be effectively quantified in the early development stages and used to align and tailor organizational resources to improve PD performance. The methods also provide the benefit of being implementable with little disruption to existing processes as they align closely with current industry practices

Concepts for design of an energy management system incorporating dispersed storage and generation

New forms of generation based on renewable resources must be managed as part of existing power systems in order to be utilized with maximum effectiveness. Many of these generators are by their very nature dispersed or small, so that they will be connected to the distribution part of the power system. This situation poses new questions of control and protection, and the intermittent nature of some of the energy sources poses problems of scheduling and dispatch. Under the assumption that the general objectives of energy management will remain unchanged, the impact of dispersed storage and generation on some of the specific functions of power system control and its hardware are discussed

A Strategic Approach to Enhancing Sustainable Practices in Public Building Projects :a Case Study of Indonesian Local Authorities

In the last few decades, there has been well documented evidence that the performance of the public building projects in local authorities in Indonesia does not fully meet the expectation of the stakeholders involved and demonstrates sustainable practices. This mediocre performance impacts on the competitiveness of building industry, and therefore would require the development of a strategic approach to address these fundamental structural and cultural issues. The strategic approach, which facilitates sustainable practices, to a large extent, depends on the local priorities, goals and success criteria, which are dynamic and influenced by the expectations of various stakeholders involved in the procurement of public buildings. This research aims to develop a conceptual framework that will help local authorities to enhance sustainable practices of public building management. The empirical research work adopted case study strategy involving interviews with 24 public building practitioners and investigation of building defects on 34 projects. This research proposes LACU model, which represents a triangular relationship between contractors, local authorities and building end-users to illustrate the interactions between parties when undertaking their tasks throughout the project lifecycle. A framework of Sustainable-Dynamic Capabilities was developed and applied to enhance understanding of sustainability provisions in public building development. Based on this framework and stakeholders’ mapping illustrated by LACU model, this research has enhanced understanding on strategies of local authority to implement sustainable practices on public building projects. A template analysis through interview transcripts has been adopted to identify strategic approaches of local authority to deliver successful project by determining the roles of stakeholder at three different levels, provincial, regency or city and special authority. This research provides a novel empirically-based guidance for the local authorities to undertake sustainable public building procurement throughout project life cycle by adopting strategic approaches, such as employing innovative construction method, appropriate policy intervention by local leader, and changing business orientation