Digital enterprise solution for integrated production planning and control

Abstract

Digital enterprise technologies combined with sophisticated optimization algorithms can significantly contribute to the efficiency of production. The paper introduces a novel approach for integrated production planning and control, with the description of the mathematical models and solution algorithms. The deterministic optimization algorithms are complemented by a discrete-event simulation system to assess solution robustness in case of disturbances. The methods are illustrated by describing two prototype systems and by some experimental results obtained in an industry initiated project.

Inter-enterprise architecture as a tool to empower decision-making in hierarchical collaborative production planning

“…A number of authors: [18,21,23,27,30,31,32,33,34,35,36,37,38,39] have identified a number of unexpected events and partially or completely agree with Darmoul et al [26]. In the literature, an additional specific unexpected event, production time variation, has also been proposed [ 21,23,25,31,37,38]. This event can be added to the "production" typology.…”

An optimisation approach for capacity planning: modelling insights and empirical findings from a tactical perspective

“…Due to complex production processes and long lead times, production often starts before the overall project design has been completed (Monostori et al, 2010). Management must rely on a rough estimation of the impact of an incoming order on resource utilisation and eventually must adjust capacity, as micro process planning (i.e., detailed technological planning of production activities that result in manufacturing instructions - Giebels, 2000) has not been performed yet (Zijm, 2000;Grabenstetter & Usher, 2014).…”

“…In practice, order acceptance and capacity planning decisions are often functionally separated, according to Ebben et al (2005) and Huang et al (2011), since the sales department is responsible for order acceptance and the production department takes care of production and capacity planning. For instance, Monostori et al (2010) affirm that project planners typically try to sequence activities as early as possible, relying on the conventional wisdom that it can never be wrong to get work done early.…”

Integrated Process Planning and Scheduling and Multimode Resource Constrained Project Scheduling: Ship Block Assembly Application

“…Solutions obtained at this level are suboptimal at the multiple facility level. In order to obtain an optimal solution at the latter level, the scope of optimisation must be enlarged to model the multiple facility supply chain of the enterprise as a whole, including the interaction with suppliers and customers; see for example (Laínez et al, 2010), Munõz et al , (2011), Stray et al, (2006), and Monostori et al, (2010).…”