Resource capacities

The requirements for short-term planning, especially with regard to campaignhandling as well as the need to consider sequence-dependent setup and finite resource capacities on most resources lead to the selection of the PP/DS optimizer as the most suitable planning method. In addition to the optimizer, PP/DS offers numerous heuristics for automating production planning and detailed scheduling tasks. 

For SNP relevant resources, however, integration issues arise due to different time profiles used by SNP, which is based on a periodic time profile with, in the scenario at hand, monthly time buckets, and PP/DS, which utilizes a continuous time representation of the planning horizon. This means that the time-continuous resource capacity profiles used in PP/DS, which are usually synchronized with the... 

Available resource capacity for SNP planning is reduced by the capacity consumption of PP/DS planned orders. 

Resource capacity consumption by SNP planned orders is not considered for PP/DS planning. 

Planned orders are place holders for process orders that have yet to be checked for planning feasibility by detailed scheduling. In a hierarchical planning model they are interpreted as a hint to the details planner that they should create and schedule a process order. They are often the result of an automated MRP (material requirements planning) run that is based on planned independent requirements and does not consider resource capacities. 

The additional capacity restriction (3.98) accounts for the capacity of the shared resource. In order to determine shared-resource capacity, restriction (3.99) can be used if the number of equipment units is correlated with the number of production lines installed at a plant. In combination with the integrality restriction (3.100) it enforces the step-wise increase of the shard resource capacity in line with the development of overall plant capacity. For example, if for every three production lines one equipment unit is to be installed, the second unit will be installed once the fourth production line is put into operation. If the model is to select the number of equipment units independently, restriction (3.99) has to be deactivated. Finally, for the option to temporarily shut down production lines capacity constraint 24 needs to be modified as shown above. 

The integration of capital expenditures for the shared resources as shown in equation (3.11a) rests on the assumption that the number of equipments is correlated to the number of production lines. If the model can independently select the shared resource capacity, it is theoretically possible that the number of shared resources operated increases while the number of production lines used decreases. In this case a separate calculation of the investment expenditures for shared resources is required to avoid that "negative" capital expenditures from capacity reductions that are eliminated via the non-negativity constraint (3.54) offset the expenditures for shared resource installations. 

The vision of the strategy is to create knowledge and human resource capacity that will develop high-value commercial activities in H FC technologies utilising local resources and existing know-how. 

The ABA s Central Office is working with the U.S. Department of Health and Human Services Office of Public Health Emergency Preparedness to establish and maintain a real-time burn bed availability program for the nation. In the recent past, the ABA worked with the U.S. Army Institute of Surgical Research on a burn bed resource capacity project. The ABA Central Office will continue to work with HHS and others to develop and maintain a real-time burn bed resource capacity reporting system. 

Resource Capacity The number of elevators and the specific floors serviced by each elevator. 

The third component of APS is order promising, which lies at the center of the transaction-based aspect of APS systems. This component is designed to suggest realistic promise dates for customer orders. The process, sometimes referred to as capable-to-promise (CTP), involves testing the customer s request date for feasibility and, if the date cannot be met, calculating the earliest date that it can be met. This is done based on available and projected inventory and available resource capacity. 

This chapter addresses the control function. First, it introduces several important concepts relating to sensory-motor control, accuracy of movement, and performance resources/capacities. Second, it provides an overview of apparatuses and methods for the measurement and analysis of complex sensory-motor performance. The overview focuses on measurement of sensory-motor control performance capacities of the upper-limbs and by means of tracking tasks. 

In task analysis, it is common practice to distinguish between stress and strain. However, these terms are sometimes used interchangeably and confusedly. In this chapter, stress refers to a condition that may lead to an adverse effect on the body, whereas strain refers to the effect of stress on the body. For example, working at a computer job in dim lighting often leads to headaches. The dim lighting is considered the stress, and the headache is the strain. The term stressor is also widely used as a synonym for stress. Strain has often been wrongly called stress. These terms must be clearly defined to determine which factors are causative ones (stresses) and which are consequences (strains). Stress is determined by task demands, while strain is determined by the amount of physical resources expended beyond some tolerable level, defined by the person s resource capacities. The stress-strain principle is pivotal to task analysis when one is concerned with errors, cumulative traumas, and injuries in the workplace and is applicable to task situations where task demands are likely to exceed human resource capacities. 

One of the key objectives of DDSC is to reduce demand amplification as it brings extra costs and inefficiencies like extra resource capacity, higher inventory levels, etc. Taylor (2000) reviews the effect of demand amplification in the supply chain and also proposes a practical approach to eliminate it through a seven step process. A pilot test was performed in UK automotive industry and showed an increase from 70 to 100% on the composite measure of delivery to time along the supply chain, and also a reduction of 30% in total supply chain inventory. 

The order-promising process employed partitions the due date time horizon into three intervals fixed product, flexible product and flexible resource. For the fixed product interval, which spans from approximately the present time to two weeks into the future, resources, in the form of manufacturing orders (MO) are fixed. An MO specifies the production quantity for each product at each assembly line in each factory. That is, a fixed production schedule is set, which takes into account both production capacity availability and critical material availability. Having a fixed schedule stabilizes production dynamics in the near term and allows for the required materials to be set up and put in place. Any order commitments made for this time interval must fit within the fixed production schedule. In the flexible product interval, two kinds of resources, capacity and material, are considered. The capacity consists of both production capacity in different factories and transportation capacity from factories to sales subsidiaries. The production capacity is given daily at factory level in terms of machine-hour and manpower availability, while the transportation capacity is specified as weekly maximum quantity from factories to sales subsidiaries. The weekly availability of individual critical materials is aggregated into finished good level availability grouped based on the bill of material (BoM). Any order commitments made for this time interval must satisfy the capacity and material availability constraints. The flexible product interval spans from approximately two weeks to two months into the future. For the flexible resource interval, which covers due dates more than two months into the future, the only constraint considered is production capacity. This interval starts beyond the resource lead times so any resource commitments can be met. 

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