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Demand flow technology (DFT) is a strategy for defining and deploying business processes in a flow, driven in response to customer demand. DFT is based on a set of applied mathematical tools that are used to connect processes in a flow and link it to daily changes in demand.
A lead time is the latency between the initiation and completion of a process. For example, the lead time between the placement of an order and delivery of new cars by a given manufacturer might be between 2 weeks and 6 months, depending on various particularities.
A supply chain responsiveness matrix is a tool that is used to analyze inventory and lead time within an organization. The matrix is one of a number of value stream mapping tools. [1] The matrix is represented by showing lead time along the x-axis and inventory along the y-axis. The result shows where slow moving stock resides.
The first research towards defining order fulfilment strategies was published by Hans Wortmann, [1] and was continued by Hal Mather [2] in his discussion of the P:D ratio, whereby P is defined as the production lead time, i.e. how long it takes to manufacture a product, and D is the demand lead time. D can be viewed as: The lead time quoted by ...
Value-stream mapping, also known as material- and information-flow mapping, [1] is a lean [2]-management method for analyzing the current state and designing a future state for the series of events that take a product or service from the beginning of the specific process until it reaches the customer.
In operations management and industrial engineering, production flow analysis refers to methods which share the following characteristics: Classification of machines; Technological cycles information control; Generating a binary product-machines matrix (1 if a given product requires processing in a given machine, 0 otherwise)
Flow Shop Ordonnancement. Flow-shop scheduling is an optimization problem in computer science and operations research.It is a variant of optimal job scheduling.In a general job-scheduling problem, we are given n jobs J 1, J 2, ..., J n of varying processing times, which need to be scheduled on m machines with varying processing power, while trying to minimize the makespan – the total length ...
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