Hur ett tvärfunktionellt samarbete kan motverka stuprörsstrukturer : Kommunikationens roll i det organisatoriska gränssnittet mellan olika avdelningar

Stovepipes, or also called silos, appear in many different organizations and sectors and contribute to problems when employees or managers tend to look more to their own, or the individual departments, objectives rather than to the organizations. The purpose of this study was to identify different communicative factors that promote stovepipes in order to further identify the most critical factor to disarm. A case study has been done at a selected company, with a stovepipe structure, in order to achieve the purpose of the study. The case study has included interviews and observations to identify different problem areas which then have been compared with three communicative factors identified in previous studies. The factor that had the most connections to the problem areas have been considered the most critical factor. The result of the study indicates that “A lack of understanding each other's work” is the most critical factor in stovepipe structures and that it can be prevented by following five recommendations: bring up positive collaboration continually, raise problems with each other instead of with others, identify different communication paths in and between the departments, implement a long-term model for preventing stovepipes and set up workshops between the involved departments. The conclusion of the study is that stovepipes create several undesirable effects in the organization but that the efforts to counter these problems do not have to be complicated. Following five small steps into a better collaboration and communication can be enough to be on your way to a better organizational structure.

Least Squares Approach to Inverse Problems in Musculoskeletal Biomechanics

Inverse simulations of musculoskeletal models computes the internal forces such as muscle and joint reaction forces, which are hard to measure, using the more easily measured motion and external forces as input data. Because of the difficulties of measuring muscle forces and joint reactions, simulations are hard to validate. One way of reducing errors for the simulations is to ensure that the mathematical problem is well-posed. This paper presents a study of regularity aspects for an inverse simulation method, often called forward dynamics or dynamical optimization, that takes into account both measurement errors and muscle dynamics. The simulation method is explained in detail. Regularity is examined for a test problem around the optimum using the approximated quadratic problem. The results shows improved rank by including a regularization term in the objective that handles the mechanical over-determinancy. Using the 3-element Hill muscle model the chosen regularization term is the norm of the activation. To make the problem full-rank only the excitation bounds should be included in the constraints. However, this results in small negative values of the activation which indicates that muscles are pushing and not pulling. Despite this unrealistic behavior the error maybe small enough to be accepted for specific applications. These results is a starting point start for achieving better results of inverse musculoskeletal simulations from a numerical point of view.