Production Network Planning and Controlling

Given the supply-chain context of this book, we will consider only the management of independent-demand items—i.e., those items that move between firms in the supply chain. Throughout this book, we focus on issues related to node-to-node relationships in the supply chain, consistent with the framework developed in Chapter 1 that defines a supply chain as a network of nodes. Dependent demand involves "within-node" effects and is outside the scope of this book, but is discussed extensively in books on production/operations planning and control systems (e.g., Vollmann et al., 2005 or Chapman, 2006, which also contains an excellent discussion on hybrid systems that combine appropriate elements of MRP and kanban control). Note, however, that the classification of an item as an independent-demand item or a dependent-demand item is not an absolute characterization. Rather, it only makes sense in context. For example, to the company that assembles the cell phones, the keypad is clearly a dependent-demand item, provided that its only demand is derived from the production schedule for cell phones (i.e., not from sales of keypads as stand-alone items). To the firm that produces the keypads and sells them to various cell phone manufacturers, however, the keypad is an... 

For specialty chemicals production networks, the planning and controlling process has to combine the site perspective and the value chain perspective. Most specialty chemicals companies have a division/business unit organization and operate sites shared by several divisions. While each division can cover the value chain perspective individually, for example by integrating the above-mentioned indicators into controlling processes, the site perspective requires cross-divisional coordination to avoid suboptimal solutions. Different options ranging from centralized to decentralized setups exist to do so (cf. Hayes and Wheelwright 1984, pp. 120-125). 

Autonomous Control in Production Networks These autonomous control methods are not limited to single production systems. Furthermore, they can be applied to more complex systems like production networks. Production networks are characterized by multiple production facilities which are interconnected via transport systems. Production networks focus on integrated planning of geographical dispersed and company spanning processes as well as the planning of usage of common resources... 

In the present work, we focus on the operational planning and control of integrated production/distribution systems under product demand uncertainty. For the purposes of our study and the time scales of interest, a discrete time difference model is developed. The model is applicable to networks of arbitrary structure. To treat demand uncertainty within the deterministic supply chain network model, a receding horizon, model predictive control approach is suggested. The two-level control algorithm relies on a... 

In an empirical study Vereecke and Van Dierdonck (2002) tested Fer-dow s model and found it to be valid with two exceptions it appears to be too limited in the criteria for adding plants to an existing network and lead factories were also added based on market proximity. In another study Maritan et al. (2004) used autonomy over planning, production and control decisions to validate Ferdow s model but found only weak correlations with planning decisions showing the strongest correlation. 

Planning a network of integrated chemical production sites causes various problems. Due to the interdependency of the production processes, local disturbances at a certain level of a particular production site can affect the site s performance entirely or at least downstream (inter-site effect). Moreover, due to the interconnectedness of production sites in a chemical production network, such a local disturbance can spread out on the entire SC (intra-site effect). This fypicaUy feads to increased risk costs. The organization and central control of chemical production networks aims at hmiting the effects of such disturbances. 

Wiendahl and Lutz 2002). Accordingly, additional planning task, e.g., the assignment of orders to plants or the coordination of production and transport processes, occur. First approaches have shown that autonomous control methods can be applied to production networks. The implementation of autonomous control methods may help to harmonize the material flow through the production and transport system (Scholz-Reiter et al. 2009b). 

Using the distributed control system a network of control can be built up in modular fashion. Individual process control units are applied to single plant units and communicate either with each other or with a central computer via a data highway. Via the same highway, links are also available for production management information, production planning, quality control involvement, whether on- or off-line and costing operations (von Klosterlein and Vos, 1983). 

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