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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.
Given a description of the possible initial states of the world, a description of the desired goals, and a description of a set of possible actions, the planning problem is to synthesize a plan that is guaranteed (when applied to any of the initial states) to generate a state which contains the desired goals (such a state is called a goal state).
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.
Non-conformance may be a market complaint or customer complaint or failure of machinery or a quality management system, or misinterpretation of written instructions to carry out work. The corrective and preventive action is designed by a team that includes quality assurance personnel and personnel involved in the actual observation point of non ...
RPR has been fully aligned with ITIL v3 since RPR 2.01 was released in April 2008. RPR fits directly into the ITIL v3 problem management process as a sub-process. Some organisations handle ongoing recurring problems within incident management, and RPR also fits into the ITIL v3 incident management process as a sub-process.
Interval scheduling is a class of problems in computer science, particularly in the area of algorithm design. The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be processed by some machine (or, equivalently, scheduled on some resource).
Troubleshooting is a form of problem solving, often applied to repair failed products or processes on a machine or a system. It is a logical, systematic search for the source of a problem in order to solve it, and make the product or process operational again. Troubleshooting is needed to identify the symptoms.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]