Discusses the movement away from hierarchical organizational structures towards flatter, heterarchical, structures which is reflected in the growing interest in distributed manufacturing control systems. Traditional hierarchical control systems are limited by the breadth, quantity and timeliness of information needed for their operation. Distributed, heterarchical, control systems overcome these hierarchical limitations but, concurrently, forfeit advantages of the hierarchy including analytically optimal loading patterns and centralized pristine data tracking. Classifies existing research into four categories and documents a progression of heterarchical control approaches to inject some of the advantages of the traditional hierarchy into new heterarchical frameworks. Concludes that neither hierarchical nor heterarchical control structures are ideal in their pure form and, hence, proposes a modified structure, called the quasi‐heterarchical control system, which is a combination of, and a compromise between, pure hierarchy and pure heterarchy.

Traditional capacity planning modelling techniques focus on the steady-state behaviour of a system. This is because transient behaviour complicates the problem, both conceptually and analytically, and solutions tend to be time consuming. Nevertheless, the transient behaviour of a system is often of equal consequence to that of the steady-state behaviour and requires methods for characterization. Further, today's increasingly powerful personal computers allow complex, dynamic behaviours to be modelled in a timely manner. This paper presents a model for incorporating dynamic behaviour into capacity planning. The model is demonstrated through a case study of a telephone order entry system.

BatteUe-' Memorial Institute, nor any oftheir employees, makes any warranty, express or implied, or assumes any legal-liability or responsibility for the accuracy, completeness, .or usefulnessof any hifohnation, appa-mtus, product, or processdisclosed; orrepresents that its use would not infripge phvately owded rights. Reference herein to any specific commercial product;process, or Serviqby &e name, trademark, manufacturer, or otherwise does not-nea+ady constitute or imply its endorsement, rymmendation,.or favoring by the' United States GoveFment or any rtgency thereof, or Battelle Memorial Institute.

No abstract

0_81O"IRgL-9(DV-_Ifl _o_muo3 _pun ,¢B_u_I jolu_um_d_I "S'fl _ql _o_ _ _I £661_qo_:_3 s._rI "EI "_l u_mIq_zs"f "EI uo!1_.m_q_juooe8 aSalOnN-uoN "IV'_O(I .mj iapolMuo!llSUS,U, osJOJ_l.mA_ SummaryThe Pacific Northwest Laboratory (PNL) was tasked by the U.S. Department of Energy Albuquerque Field Office (DOE-AL) to develop a workforce assessment and transition planning tool to support integrated decision making at a single DOE installation. The planning tool permits coordinated, integrated workforee planning to manage growth, decline, or transition within a DOE installation. The tool enhances the links and provides commonality between strategic, programmarie, and operations planners and human resources. Successful development and subsequent complex-wide implementation of the model will also facilitate planning at the national level by .enforcing a consistent format on data that are now collex.'ted by installations in corporate-stw..eific formats that are not amenable to national-level analyses.The workforce assessment and transition planning tool consists of two components: the Workforce Transition Model and the Workforce Budget C_..nstraintModel. The Worlcforee Transition Model, the preponderant of the two, assists deelsion makers to identify and evaluates alternatives for mmsitioning the current workforce to meet the skills required to support projected workforce requirements. The Workforee Budget Constraint Model helps estimate the number of personnel that will be affected given a workforee budget inca'ease or decrease and assists in identifying how the corresponding hirings or layoffs should be distributed across the common occupational classification system (COCS) occupations. The conceptual models and the computer implementation are described.iii