Decision table

As process plants become more complex, it becomes apparent that it is not possible to rely exclusively on the process worker s skills and memory required to perform the task. Job aids and procedures are devices which aim to reduce the need for human retention of procedures and references as well as the amount of decision making required. Job aids assume a variety of formats including flowcharts, checklists, decision tables, etc., while procedures refer to other systems of documentation such as standard operating instmctions and emergency procedures. 

The format of the procedure is also important in this respect. There may be situations where alternatives to prose are more efficient and acceptable. A flow diagram or a decision table may help the process worker to concentrate more easily on what indications are presented, and what decisions and control actions he or she has to make (see Wright. 1977). 

In order to set up a harmonized framework for the regulation of plant protection products in the EC, Council Directive 91/414/EEC of 15 July 1991 concerning the placing of plant protection products on the market was adopted and implemented in all Member States. Six annexes were established within this Directive, providing the basis for the harmonization of registration procedures and regulatory decisions (Table 1). 

Inductive methods, such as check lists, Failure Mode and Effect Analysis (FMEA), event trees, decision tables, Analysis of Potential Problems (APP). These methods proceed from an initial cause of the deviation and construct a scenario ending with the final event. They are based on questions of the type What if ... 

Figure 1.6 Decision table for the collision of a car with a deer [8].

The hazard identification methods presented in Sections 1.5.1 to 1.5.6 above are all based on strongly systematic procedures. In the check list method, the systematic is provided by the check list itself. The comprehensiveness can be verified in the matrix (see Figures 1.4 and 1.5). With the FMEA, the systematic is provided by the division of the system into elements and the failure modes considered. In the HAZOP study, the systematic stems from the division of the plant into nodes and lines, then the systematic application of the keywords. With the decision table method, the systematic is inherent to the table. For the FTA and ETA, the systematic is given by the tree and the logical ports. Nevertheless, the work of the team must be traceable, even by persons who did not participate to the analysis. Thus, it is recommended to also document the hazards that were not considered as critical. 

As Chapters 8 and 9 pointed out, human resources are among a pharmacy s most valuable assets. Employee wages can account for one of the pharmacy s greater operating expenditures (see Chapter 15). Employees, however, should not be viewed as a cost but as an essential asset for organizational success. The ramifications of executing a good performance appraisal system extend to most human resources decisions. Table 10-1 summarizes some important points about the need for performance appraisals. 

In general, progress in drug development depends on data obtained from analytical instruments. Thus, how this information is derived and provided to decision makers is critical to the success of the pharmaceutical industry. LC/MS technologies have effectively and uniquely supported the productivity (quantitative processes) and efficiency (qualitative processes) needs of drug development. Future issues appear to be directed toward enhancement of the information-gathering process that focuses on the relationship between data and decision (Table 8.1). 

Table 6.6 is provided as a final aid for protective glove selection decisions. Table 6.6 identifies the preferred glove types as well as those not recommended for use with pesticide formulations containing various carrier solvent types. The glove types identified as preferred are those that consistently provide the best permeation resistance to pesticide formulations and undiluted carrier solvents within each chemical classification identified. The glove types identified as not recommended are those that consistently provide very poor permeation resistance. Also note that the recommendations in Table 6.6 are... 

Once acquired, there are many ways of representing the knowledge in the knowledge base, including production rules, frames, semantic networks, decision tables, and trees and objects. Probably the most common methodology is the production rule, which expresses the relationship between several pieces of information by way of conditional statements that specify sections under certain sets of conditions, for example ... 

Decision tables display information used to make emergency operating decisions in an easily accessed format. They are also sometimes referred to as contingency tables. 

Figure 6-11. An example of a decision table that could appear in an EOP or...

Figure 1. Decision table to evaluate quality of carbonate analytical data from differences between total dissolved carbonate concentrations equal to the sum of analyzed carbonate species, as analyzed directly, and as modeled from pH and alkalinity.

Steudel, H. J, and Tollers, G. V. (1985), A Decision Table Based Guide for Evaluating Computer-Aided Process Planning Systems, in Proceedings of 1985 ASME Winter Annual Meeting (Miami Beach), pp. 109-119. 

TABLE 3 Decision Table for the Task of Planning How to Cut a Part in a CNC Lathe... 

Key Supply Chain Decisions Table 2.7 MRP calculations for chip... 

How should the order be produced what mix of make vs. buy should be used to minimize costs This decision can be made by framing the problem as a linear program and using available solution packages, e.g., the Solver package in Excel. To frame the problem, we define a set of decisions X, i = 1, 2, 3 as the amount of products 1, 2, and 3 that are made in house and Xj2, i = 1, 2, 3 as the amount of products 1, 2, and 3 that are subcontracted. Let Q, i = 1, 2, 3 andy =1,2 refer to the costs associated with each of the decisions (Table 4.6) and dj refer to the quantity of product i demanded. 

QianY, Liang J, Dang C. Converse approximation and rule extraction from decision tables in rough set theory. Comput Mathematics 2008 55 1754—1765. 

Nasiri JH, Mashinchi M. Rough set and data analysis in decision tables. J Uncertain Syst 2009 3 232-240. 

Xiao J-M. New rough set approach to knowledge reduction in decision table[s]. Proc Int Conf Mach Learn Cybem 2004 4 2208-2211. 

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