On the Interface Between Operations and Human Resources Management

Operations management (OM) and human resources management (HRM) have historically been very separate fields. In practice, operations managers and human resource managers interact primarily on administrative issues regarding payroll and other matters. In academia, the two subjects are studied by separate communities of scholars publishing in disjoint sets of journals, drawing on mostly separate disciplinary foundations. Yet, operations and human resources are intimately related at a fundamental level. Operations are the context that often explains or moderates the effects of human resource activities such as pay, training, communications and staffing. Human responses to operations management systems often explain variations or anomalies that would otherwise be treated as randomness or error variance in traditional operations research models. In this paper, we probe the interface between operations and human resources by examining how human considerations affect classical OM results and how operational considerations affect classical HRM results. We then propose a unifying framework for identifying new research opportunities at the intersection of the two fields

Design and control of agile automated CONWIP production lines

In this article, we study the design and control of manufacturing cells with a mix of manual and automated equipment, operating under a CONWIP pull protocol, and staffed by a single agile (cross-trained) worker. For a three-station line with one automated station, we fully characterize the structure of the optimal control policy for the worker and show that it is a static priority policy. Using analytical models and extensive simulation experiments, we also evaluate the effectiveness of practical heuristic control policies and provide managerial insights on automation configuration design of the line. This characterization of the worker control policy enables us to develop managerial insights into the design issues of how best to locate and concentrate automation in the line. Finally, we show that, in addition to ease of control and greater design flexibility, the CONWIP protocol also offers higher efficiency and robustness than does the push protocol. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/61525/1/20325_ftp.pd

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

Essays on resource flexibilities in services

Service firms unable to store services, constantly search for strategies to minimize supply-demand imbalance in resources. Escalating costs, nursing shortages, and process inefficiencies have led the US healthcare system to operate at near-full capacity and maintain high utilization levels. Even though hospitals often function at full capacity, they are expected to treat all patients due to legal, social and moral obligations. Hospitals use a combination of resource flexibility strategies to reduce supply-demand imbalance due to demand variability. In this dissertation, we analyze the benefits of using flexibility strategies on critical resources such as labor (nursing staff), equipment (bed spaces), and patient assignment to contain demand variability in the short-term. Staffing flexibility, often referred to as cross-training, is widely used in many service firms to increase labor utilization, morale, and job enrichment. Although cross-training is cost-efficient, cross-trained nurses are less productive in new units. In the first essay, we analyze the cost savings vs. productivity changes when using staffing flexibility in hospitals. We find that productivity of cross-trained nursing staff has a significant effect on the optimal amount of cross-training. There is also an interaction effect between productivity of cross-trained nurses, cross-training cost, and demand variability. In the second essay, we add a second resource flexibility strategy referred to as demand upgrades. Patients who are typically treated in a simple unit can be upgraded to a complex unit when beds are unavailable in the simple unit. We compare the impact of these two resource flexibility strategies on a hospital’s ability to meet stochastic patient demand. We also look at the impact of the timing of capacity and staffing decisions on system performance. In the third essay, we develop a resource flexibility strategy framework that utilizes internal resources (labor, equipment, and patient assignment) to efficiently manage different levels of demand variability. The insights, issues and implications needed for managers to implement flexibility models are also presented in the third essay. Thus, this dissertation has analyzed the benefit, trade-offs, limitations, and outcomes in implementing critical resource flexibility strategies in hospitals to minimize supply-demand imbalance and address short-term demand variability

Management of Worksharing Systems

Worksharing occurs in serial manufacturing when machines are not uniquely assigned to workers. For example, two workers can operate three machines by alternating usage of the middle one. In some other worksharing systems operators move down the line carrying an item (or batch) with them, working on it at each machine until they are met by another worker who is coming back upstream. The work is then handed off even if the operation is underway. "Bucket Brigade" and "TSS" are worksharing systems based on this idea. This paper examines worksharing in a variety of situations, including unequal work content across machines, uncertain processing times, unequal workers, handoffs with and without preemption, and a range of machine-to-worker ratios. Some systems restrict workers to "zones" of machines. Work zones must overlap if sharing is to occur. The appropriate size of the overlapis shown to depend on the circumstances. Inventory-based rules to control access to shared machines are demonstrated to increase productivity when processing times vary. Worker sequence is found to be quite important; Slowest-to-Fastest is recommended for some situations, but is shown to perform poorly in others. Finally, the issue of whether or not to allow preemption is shown to have a large impact on productivity if inventory is not allowed, and to strongly affect the choice of designs when inventory is allowed. With and without preemption, proper combinations of worker sequence, zone size, and production control rules are shown to nearly eliminate idle time.worksharing, serial production lines, cross training, bucket brigade