Aplicación de modelos de mejoramiento de procesos utilizando estudios de tiempos en el área de licitaciones de la empresa Mapfre Seguros

Trabajo de InvestigaciónEl trabajo va orientado a la elaboración de un plan de mejoramiento en un área específica de la empresa Mapfre Seguros. Este objetivo se logró después de hacer un análisis de la situación actual del área a través de varias herramientas de calidad, diagnóstico del proceso del área mediante un estudio de tiempos, y finalmente se realiza el diseño del plan de mejoramiento que permite perfeccionar el proceso del área investigadaINTRODUCCIÓN 1. GENERALIDADES 2. RECOPILACIÓN Y ANÁLISIS DE LA INFORMACIÓN 3. DIAGNÓSTICO DEL ÁREA DE LICITACIONES 4. PROPUESTA DE MEJORAMIENTO 5. CONCLUSIONES 6. RECOMENDACIONES BIBLIOGRAFÍA ANEXOSPregradoIngeniero Industria

A strategy for evaluating occupational risk factors of musculoskeletal disorders

There is a large and increasing incidence of work-related muscoloskeletal disorders, both upper extremity cumulative trauma disorders and low back pain. Several occupational risk factors have been linked with the development of musculoskeletal disorders. In order to identify the known occupational risk factors associated with a specific job, an analysis procedure is described to help identify ergonomic risk factors in the workplace. Job analysis should be one part of an overall ergonomics control program. Once the ergonomic risk factors have been documented, the ergonomics committee can use that information to begin developing solutions that will decrease or eliminate the identified risk factors. When placing a worker who is returning to the workforce after recovering from an injury, health care professionals can also use the information from the job analysis to assist in matching up task demands with worker capabilities and limitations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45019/1/10926_2005_Article_BF01078930.pd

Effect of replenishment and backroom on retail shelf-space planning

Shelf-space optimization models support retailers in making optimal shelf-space decisions. They determine the number of facings for each item included in an assortment. One common characteristic of these models is that they do not account for in-store replenishment processes. However, the two areas of shelf-space planning and in-store replenishment are strongly interrelated. Keeping more shelf stock of an item increases the demand for it due to higher visibility, permits decreased replenishment frequencies and increases inventory holding costs. However, because space is limited, it also requires the reduction of shelf space for other items, which then deplete faster and must be reordered and replenished more often. Furthermore, the possibility of keeping stock of certain items in the backroom instead of the showroom allows for more showroom shelf space for other items, but also generates additional replenishment costs for the items kept in the backroom. The joint optimization of both shelf-space decisions and replenishment processes has not been sufficiently addressed in the existing literature. To quantify the cost associated with the relevant in-store replenishment processes, we conducted a time and motion study for a German grocery retailer. Based on these insights, we propose an optimization model that addresses the mutual dependence of shelf-space decisions and replenishment processes. The model optimizes retail profits by determining the optimum number of facings, the optimum display orientation of items, and the optimum order frequencies, while accounting for space-elasticity effects as well as limited shelf and backroom space. Applying our model to the grocery retailer's canned foods category, we found a profit potential of about 29%. We further apply our model to randomly generated data and show that it can be solved to optimality within very short run times, even for large-scale problem instances. Finally, we use the model to show the impact of backroom space availability and replenishment cost on retail profits and solution structures. Based on the insights gained from the application of our model, the grocery retailer has decided to change its current approach to shelf-space decisions and in-store replenishment planning