Enabling flexibility through strategic management of complex engineering systems

”Flexibility is a highly desired attribute of many systems operating in changing or uncertain conditions. It is a common theme in complex systems to identify where flexibility is generated within a system and how to model the processes needed to maintain and sustain flexibility. The key research question that is addressed is: how do we create a new definition of workforce flexibility within a human-technology-artificial intelligence environment? Workforce flexibility is the management of organizational labor capacities and capabilities in operational environments using a broad and diffuse set of tools and approaches to mitigate system imbalances caused by uncertainties or changes. We establish a baseline reference for managers to use in choosing flexibility methods for specific applications and we determine the scope and effectiveness of these traditional flexibility methods. The unique contributions of this research are: a) a new definition of workforce flexibility for a human-technology work environment versus traditional definitions; b) using a system of systems (SoS) approach to create and sustain that flexibility; and c) applying a coordinating strategy for optimal workforce flexibility within the human- technology framework. This dissertation research fills the gap of how we can model flexibility using SoS engineering to show where flexibility emerges and what strategies a manager can use to manage flexibility within this technology construct”--Abstract, page iii

Calibrating cross-training to meet demand mix variation and employee absence

We address the problem of determining the cross-training that a work team needs in order to cope with demand mix variation and absences. We consider the case in which all workers can be trained on all tasks, the workforce is a resource that determines the capacity and a complete forecasting of demand is not available. The demand mix variation that the organization wants to be able to cope with is fixed by establishing a maximum time to devote to each product. We contend that this approach is straightforward, has managerial practicality and can be applied to a broad range of practical scenarios. It is required that the demand mix variation be met, even if there are a certain level of absences. To numerically solve the mathematical problem, a constraint-based selection procedure is developed, which we term CODEMI. We provide illustrated examples demonstrating solution quality for the approximation, and we report on an illustrative set of computational cases. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.Peer ReviewedPostprint (published version

Optimization of process integration and multi-skilled resource utilization in off-site construction

Traditional approaches in construction project management assign each process to a trade contractor with an individual specialisation, and trades with the greatest work content (bottlenecks) have a significant influence on the progress rate of projects. A system with integrated processes, however, is able to function dynamically in response to variability in product demand and labour resources. This investigation aims to compare and contrast cross-training strategies that are applicable to off-site construction in order to create multi-skilled resources. To this end, the optimal number of additional skills was formulated as a constrained optimization problem. Then, production data from two prefabricated production facilities in Melbourne and Brisbane, Australia were used to construct a total of 1080 simulation experiments. Tangible performance metrics of systems were used to compare process integration strategies and use of multi-skilled resources. Findings show that choosing optimal process integration architecture depends on the level of capacity imbalance and processing time variability. This investigation optimises the decision making on process integration in off-site construction networks

Investigations into Flexible Operational Paradigms to Mitigate Variability.

The work of this dissertation is concerned with the study of the effectiveness of paradigms of production flexibility to either improve system performance or mitigate system risk. A brief introduction to the concept of operational flexibility is provided in Chapter I. In Chapter II, we consider a cross-trained workforce on a serial production line, and we introduce a new strategy of worker cross training called a “fixed task zone chain” (FTZC) as a special type of zone based cross training. This new approach seeks to maximize the performance of a production line, in the same fashion as a standard two skill chain, but with a significant reduction in the number of skills that must be cross trained. This allows a firm to maintain nearly the same levels of throughput, but at a fraction of the cross-training and implementation costs. Chapter III targets our study of operational flexibility on the field of supply chain management. A flexible supply chain design is useful to mitigate the effect of stochastic supplier disruptions on operations and, especially, financial cash flows. The work of this chapter develops mitigation strategies for a firm to use in sourcing from flexible suppliers and demonstrates the conditions under which flexibility in the firm’s supply chain is necessary. Finally, to assist with the understanding of the flexibility paradigms, we have designed an instrument to promote the understanding of flexibility with respect to cross-training as well as to assist in its implementation. That is, we develop a hands on, active learning experience placing participants “on the job” in a serial production line of cross-trained workers where participants can: 1) learn basic concepts of operations management, production control, and workforce agility; 2) understand system responsiveness and what can be done to improve it; 3) generate creative thinking and discussion on the value of flexibility; and 4) experience first-hand foundational factory physics concepts like cycle time, throughput, and Work In Process (WIP).Ph.D.Industrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64773/1/dpwillia_1.pd

Scheduling and staffing of multiskilling of workforce in the context of off-side construction

Aim: There is an increase of interest in multiskilling research from the academy, industry and governmental authorities. Multiskilling of a workforce refers to enhancing flexibility of production by enabling labor to be reallocated in response to change in production priorities during the production horizon. Production priorities can change for several reasons; however, this study considers changes due to alterations in bottleneck configurations. The aim of this research is to investigate the extent to which operational benefits associated with different multiskilled resource management policies pertaining to bottleneck configurations can be achieved in off-site construction. To achieve this aim, first the multiskilling of a workforce in an off-site construction context should be understood as it is a complex matter in both conception and application. Second, an appropriate scheduling method should be developed to allocate an existing workforce to the right tasks, based on their skill level and set, during the production makespan. Third, a staffing platform should be developed to facilitate recruiting and hiring of a multiskilled workforce with an appropriate skill level and set. Methodology: In the Chapter 2 a two-stage paper-screening methodology was used to collect relevant papers in the literature review section. A flow-shop-based optimization methodology is used in the Chapter 3 to schedule multiskilled crew during the production makespan to achieve the production objective. A quadratic resource allocation model was developed to allocate a workforce to different tasks with consideration of the scheduling cost. A piece-wise linearization method is deployed to linearize quadratic constraints and decrease solution time. The Chapter 4 adopts a hybrid method including optimization and multi-criteria decision-making techniques to advise the best multiskilling strategy by comparing the performance of existing multiskilling staffing configurations based upon a range of existing qualitative and quantitative criteria. PROMETHEE is recognized as a suitable multicriteria decision-making approach to incorporate qualitative criteria. A flow shop scheduling method is used to obtain an optimized performance from alternatives pertaining to quantitative criteria. The Chapter 5 of this thesis presents a decision-support tool to optimize a multiskilled staffing strategy. The methodology in this chapter differs from that in Chapter 3 in that the developed staffing optimization platform explores every possible multiskilling strategy to find the optimal staffing configuration. Findings: In Chapter 2, the literature review results in the development of a construction multiskilling framework. This framework investigates multiskilling literature in conception and application. Multiskilling framework includes four main categories of multiskilling context, collateral effects, Mainstream research and strategy. A developed scheduling platform in Chapter 3 indicates that an optimal multiskilled labor allocation can lead to significantly different outcomes in terms of cost and time, based upon whether the location of the bottleneck is fixed or variable. The findings in Chapter 4 indicate that chaining and hiring a multiskilled workforce which is able to contribute to four different tasks, are the best multiskilling staffing strategies among existing ones. Sensitivity analysis pertaining to different criteria weight illustrates that the results of this investigation are stable in a wide range of alterations in the weight allocation. In Chapter 5 the decision-support tool illustrates that the optimal multiskilling strategy is highly context specific and should be customized in relation to production circumstances and data, especially the magnitude of bottlenecks. A slight alteration in the production characteristics can lead to significant changes in the optimal cross-training policy. Subjective multiskilling of a workforce could lead to counterproductive results such as a significant cost overrun. Numerical experiments indicate that if there is no extra capacity to allocate more workers to a bottleneck workstation, multiskilling of the workforce in the workstation immediately preceding the bottleneck workstation can lead to enhancement in the productivity. Contribution: The main contribution of the Chapter 2 is to identify theoretical gaps in the cross-training research and pave the way for comprehensive studies to produce more realistic multiskilling knowledge that considers both technical and managerial details. Research findings in Chapter 3, contribute to the scheduling literature by presenting an optimization platform for multi-skilled resource allocation and relocation during the makespan pertaining to the project objective. Research findings in Chapter 4 contribute to staffing literature by presenting a hybrid methodology which can encompass qualitative criteria as well. Research findings in Chapter 5 contribute to staffing literature by presenting a novel optimization platform to optimize configuration of multiskilled labor pertaining to their skill set. Chapter 3, 4 and 5 make another important contribution to the body of knowledge which is quantifying how performance measures and labor skill sets interact with each other. The decision-support tool, which is incorporated in Chapter 5, can help off-site construction industry practitioners, without a relevant academic background, to staff and schedule a workforce to achieve their production objective

Implementation of Cross-training for Multi-shift Worker Allocation

In workforce allocation, gaps between workers available and workers needed at various operations result in production delays and a loss of profitability for the manufacturer. These gaps can be reduced by overtime assignments of workers from other shifts. However, for a multiple shift planning horizon, a mix of cross-training of workers over different tasks along with overtime assignments may be a good strategy. This work develops an industry-motivated cross-training framework that identifies workers and operations for normal, overtime, and training assignments. A mixed integer programming model that integrates all three assignment tasks is formulated and solved. The production scenario consists of skill level based qualifications for workers that need to be assigned to operations in every shift. Factory floor conditions such as limits on worker levels at specific operations, scheduling restrictions and worker training protocols are also considered. The data taken into account includes parameters such as man-machine ratio, tool count, and limits on skill qualifications for workers. The output of the model provides a cross-training schedule and an assignment schedule that can be used by floor managers on a shift-by-shift basis. The MIP model is implemented in C# using the .NET framework and the IBM ILOG CPLEX Optimizer

A Novel Work-Sharing Protocol for U-Shaped Assembly Lines

Companies worldwide try to employ contemporary manufacturing systems that can cope with changes in external competitive environments and internal process variability. Just In Time (JIT) philosophy helps achieve the required resilience by its policy of having people, machines, and material just-in-time for any given process. U-shaped assembly lines (U-lines) are used to implement JIT principles. Another principle that helps achieve competitive advantage by developing a flexible workforce that responds efficiently to change is that of work-sharing. Operators share work and help each other in a dynamic and floating way, requiring little management effort to distribute workload amongst operators, or balance the assembly line. The aim of this work is to develop an effective work-sharing protocol for U-shaped assembly lines that will provide the combined advantages of U-lines and work-sharing principles. The new protocol is based on two ideas from literature - the Cellular Bucket Brigade (CBB) system, and the Modified Work-Sharing (MWS) system. To keep the focus on developing the protocol, the scope of this work was limited to two worker systems. The methodology used is to model the protocol and U-line system as a discrete event simulation model, and then use an optimization model to maximize throughput and find optimal buffer locations and levels. A physical simulation experiment was conducted in the Toyota Production Systems lab at RIT to validate the model. Once validated, computer simulation experiments were run with industry data, and results obtained were compared with existing protocols from literature. It was found that the new protocol performed at least as well as the CBB protocol, improving the output by an average of 1%, for the scenarios tested. Increase in processing speed variability as well as larger variation among workers were found to negatively impact the performance of the protocol. The results were analyzed further to understand why these factors are significant, and why there are anomalies and patterns, or lack thereof. Finally, limitations of the protocol, and opportunities for future research in the field are presented. Major limitations of the protocol are that it is difficult to comprehend, and the assumption of an assembly line divided into equal tasks is not practical in the industry

Optimization of labor allocation at a syringe production facility : design proposals

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (leaf [53]).At MD Medical (Singapore), the syringe value stream is facing escalating labor cost and high labor turnover. Therefore, optimization of the current labor resources is necessary to control the labor cost effectively without affecting the production capacity in order to stay competitive in the global context. A method used to design optimized labor allocations is outlined. Labor tasks were first categorized based on skill levels to form new job scopes. Following which, two new labor allocations were proposed. Both proposals feature flexible worker systems that reduce the response time to machines failures, as well as more focused job scopes to minimize work interruptions. New labor allocations facilitate the implementation of a skill-based pay system, which motivates employees to learn new skills. These two proposals can provide the benefits of higher production output and improved resource utilization.by Xiangyong Su.M.Eng