Hans-Otto Günther

Produktion und Logistik

Dieses Lehrbuch vermittelt eine anwendungsorientierte Einf??hrung in die industrielle Produktion und Logistik. Es behandelt die wichtigsten produktionswirtschaftlichen und logistischen Planungsprobleme und stellt die zu ihrer L??sung verf??gbaren grundlegenden Methoden im ??berblick dar. Das Buch behandelt Fragen des strategischen Produktionsmanagements, die Gestaltung der Infrastruktur des Produktionssystems, die operative Produktionsplanung und -steuerung sowie die Planung logistischer Prozesse. Auf computergest??tzte Grundkonzepte zur Produktions- und Logistikplanung, insbesondere auch auf neue Entwicklungen der ???Advanced Planning Systems???, wird ausf??hrlich eingegangen.

Mixed-Integer Linear Programming approaches to shelf-life-integrated planning and scheduling in yoghurt production

In the production of perishable products such as dairy, meat or bakery goods, the consideration of shelf life in production planning is of particular importance. Retail customers with relatively low inventory turns can benefit significantly from longer product shelf life as wastage and out-of-stock rates decrease. However, in todays production planning and control systems, shelf-life issues with regard to specific products or customers are only seldom accounted for. Therefore, the objective of this paper is to develop Mixed-Integer Linear Programming (MILP) models that integrate shelf-life issues into production planning and scheduling. The research is based on an industrial case study of yoghurt production. Relying on the principle of block planning, three different MILP models for weekly production planning are presented that apply a combination of a discrete and continuous representation of time. Overnight production and, hence, the necessity for identifying two different shelf-life values for the same production lot is included in the model formulation. Numerical experiments show that near-optimal solutions can be obtained within reasonable computational time.

Dispatching multi-load AGVs in highly automated seaport container terminals

This paper is concerned with AGV dispatching in seaport container terminals. Special attention is given to multi-load vehicles which can carry more than one container at a time. The characteristics of this complex application environment and the impact on the AGV dispatching problem are analyzed and various solution techniques considered. For practical application within an online logistics control system, a flexible priority rule based approach is developed, making use of an extended concept of the availability of vehicles. For evaluation reasons, this approach is complemented by an alternative MILP formulation. Finally, the performance of the priority rule based approach and the MILP model are analysed for different scenarios with respect to total lateness of the AGVs. The main focus of the numerical investigation is on evaluating the priority rule based approach for single and dual-load vehicles as well as comparing its performance against the MILP modelling approach.

Integrated production and distribution planning in the fast moving consumer goods industry: a block planning application

In the fast moving consumer goods industry there is an ongoing trend towards an increased product variety and shorter replenishment cycle times. Hence, manufacturers seek a better coordination of production and distribution activities. In this paper, a so-called block planning approach is presented which establishes cyclical production patterns based on the definition of setup families. For the delivery of final goods from the plants to distribution centres two transportation modes are considered, full truckload and less than truckload. The proposed mixed-integer linear optimization model minimizes total production and transportation costs. Numerical results demonstrate the practical applicability of the proposed block planning approach. In particular, a rigid and a flexible block planning approach are compared which differ by their degree of flexibility in the scheduling of the production lots.

LP-based heuristics for scheduling chemical batch processes

A mixed-integer linear programming (MILP) model for scheduling chemical batch processes is presented. Since computational times are prohibitive for most problems of realistic size, a two-stage solution procedure is suggested. In the first stage, an initial solution is derived by use of a LP-based heuristic. The proposed heuristic defines a time grid that includes only a limited number of feasible periods in which a processing task is allowed to start. Thus, the size of the original multi-period MILP model is reduced in a controlled manner and optimal solutions to the relaxed model are obtained within reasonable computational time. The second stage consists of an improvement step that aims to compress the initial schedule by left-shifting operations over the time-axis. In order to evaluate the applicability of the heuristics a number of numerical experiments were performed. It is shown that near-optimal solutions are obtained for largesize problems with only modest computational effort.

Scheduling of a multi-product batch process in the chemical industry

We present an example of a mixed-integer linear programming (MILP) model for the scheduling of a multi-product batch process occurring in the chemical industry. The batch process considered is organized in several stages. Various final products are produced out of a single feedstock by a number of chemical processes. The major scheduling objective is to minimize the makespan, i.e., to complete the required production operations within the shortest possible time. The complexity of the scheduling problem is determined by such factors as variable batch sizes, shared intermediates, flexible proportions of output goods, blending processes, sequence and usage dependent cleaning operations, finite intermediate storage, cyclical material flows, and no-wait production for certain types of products. Due to the fact that computational times are prohibitive for problems of realistic size, we developed various LP-based heuristics. The heuristics proposed are applied to relaxations of the original multi-period MILP model. Thus, computational results are obtained a magnitude faster. Furthermore, near-optimal solutions are made possible for larger problems within reasonable computational time. In order to evaluate the applicability of the heuristics, a number of numerical experiments were performed.

Campaign planning for multi-stage batch processes in the chemical industry

Abstract. Inspired by a case study from industry, the production of special chemical products is considered. In this industrial environment, multi-purpose equipment is operated in batch mode to carry out the diverse processing tasks. Often, extensive set-up and cleaning of the equipment are required when production switches between different types of products. Hence, processes are scheduled in campaign mode, i.e. a number of batches of the same type are processed in sequence. The production of chem ical products usually involves various stages with significant cumulative lead times. Typically, these production stages are assigned to different plants. A hierarchical modelling approach is presented which co-ordinates the various plant operations within the entire supply network. In the first stage, the length of the campaigns, their timing, the corresponding material flows, and equipment requirements have to be determined. At this stage, an aggregation scheme based on feasibility constraints is employed in order to reflect the limited availability of the various types of production equipment. The second stage consists of an assignment model, which allocates the available equipment units between the production campaigns determined in the first stage of the solution procedure. In the third stage, resource conflicts are resolved, which may occur if clean-out operations and minimal campaign lengths have to be considered. The proposed hierarchical approach allows a more compact model formulation compared to ot her approaches known from the literature. As a result, a very efficient and flexible solution approach is obtained. In particular, commercially available standard solvers can be used to solve a wide range of campaign planning problems arising in the chemical industry.

Realizing block planning concepts in make-and-pack production using MILP modelling and SAP APO ©

In the industrial application environment considered, different variants of a basic product type are produced using the same resources and following the same basic process plan. To support production planning and scheduling for this type of production system, the concept of block planning is introduced, which has gained considerable attention, particularly in the consumer goods industry. A block represents a pre-defined sequence of production orders of variable size. In order to demonstrate the practical applicability of the proposed block planning concept, we consider the production system of a major producer of hair dyes as a case study. We present two different implementations of the block planning concept. One utilizes the Production Planning/Detailed Scheduling module of the SAP APO

Operations planning for collect-and-place machines in PCB assembly

Collect-and-place machines represent one of the most popular types of placement machines in automated printed circuit board (PCB) assembly. For scheduling the operations of this type of machinery, a three-stage heuristic solution approach is presented. In the first stage, the feeders (component types) are assigned to locations in the magazine of the placement machine. In the second stage, based on the assignment of component feeders to magazine positions, the component placement sequence is determined. Apparently, for a collect-and-place machine, this problem is similar to the well-known vehicle-routing problem. Therefore, we adapt standard methods for vehicle-routing problems, namely savings heuristics introduced by Clark and Wright [Clark, G., & Wright, J. W. (1964). Scheduling vehicles from a central delivery depot to a number of delivery points. Operations Research Quarterly, 12, 568-581]. Finally, local search principles are applied in order to improve the feeder assignment and the component placement sequence obtained. Numerical experiments are performed in order to compare the performance of the various savings-based heuristics under different experimental settings.

Advanced planning and scheduling solutions in process industry

Thank you for downloading advanced planning and scheduling solutions in process industry. Maybe you have knowledge that, people have search numerous times for their chosen books like this advanced planning and scheduling solutions in process industry, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they cope with some malicious virus inside their laptop.