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Progress, plans, problems (PPP) is a management technique for recurring (daily, weekly or monthly) status reporting. A person reports 3-5 achievements, goals and challenges from the reporting period.
The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner.
Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields.
Example of a worksheet for structured problem solving and continuous improvement. A3 problem solving is a structured problem-solving and continuous-improvement approach, first employed at Toyota and typically used by lean manufacturing practitioners. [1] It provides a simple and strict procedure that guides problem solving by workers.
D3: Develop Interim Containment Plan: Define and implement containment actions to isolate the problem from any customer. D4: Determine and Verify Root Causes and Escape Points: Identify all applicable causes that could explain why the problem has occurred. Also identify why the problem was not noticed at the time it occurred.
The assignment problem is a fundamental combinatorial optimization problem. In its most general form, the problem is as follows: The problem instance has a number of agents and a number of tasks. Any agent can be assigned to perform any task, incurring some cost that may vary depending on the agent-task assignment.
The term "problem structuring methods" as a label for these techniques began to be used in the 1980s in the field of operations research, [8] especially after the publication of the book Rational Analysis for a Problematic World: Problem Structuring Methods for Complexity, Uncertainty and Conflict. [9]
The basic form of the problem of scheduling jobs with multiple (M) operations, over M machines, such that all of the first operations must be done on the first machine, all of the second operations on the second, etc., and a single job cannot be performed in parallel, is known as the flow-shop scheduling problem.