Here are selections of Dr. Latzko's numerous publications. They are Adobe Acrobat PDF. requiring the use of the free Adobe Acrobat Reader.
|Test it in Service Slides||This is a set of slides presented at the 17th Annual International Deming Research Seminar 21 March 2011|
|The Paperwork Factory||
Many think that the tools to assure quality are solely for the manufacturing environment. This paper shows that this is not the case. Manufacturers have service components such as purchasing, data processing, human resources, order taking, etc. where a mistake can be more costly than an error on the shop floor. Knowing the differences as well as the similarities between manufacturing and service applications allows the application of the proper methods to obtain quality outcomes. The paper describes the differences and gives a methodology to use for service component of both manufacturing and other applications.
|The Productivity Paradox||
Many managers feel they should determine their staff levels by dividing the average hours of work to be done by the average hours to do each task. This assumes that there is no variation in the doing the task. It also assumes that work arrives just in time and that each item of work takes exactly the same amount of time to process. These conditions are almost never true. Queuing theory helps us to understand why backlogs can exist in such circumstances. The paper gives a brief discussion of queuing systems (sometimes called waiting lines) and shows a simple model tht explains why 100% efficiency can get a manager in trouble under some commonly occurring conditions.
|The Process Capability in Administrative Applications||
In manufacturing, the process capability of a process is relatively easy to establish. A control chart is used to locate special causes. On eliminating the special causes, the control chart data can then be used to determine the process capability. Indexes such as Cpk are sometimes used to summarize the process capability in a single constant.
|QMS Creating a Quality Plan for Service Functions||
A major issue in non-manufacturing processes is the determination of what to measure as well as how to use the results. Following the Shewhart-Deming cycle of Learning: Plan-Do- Study-Act (PDSA) the first step is to plan a proper approach to improving quality. Often one finds that there are so many aspects to measure that one does not have the necessary resources to do them all. This paper shows a method to identify key elements to be measure, how they will be obtained, measured, and what action will be taken based on outcomes. It involves everyone in the area of study from the executive to the worker in differing degree of activity. Because of this involvement there is a substantial degree of buy-in on the part of everyone in the organization.
|Some considerations of Inventory, SMED and Shingo||
Inventory is a way to service customers just in time. Holding inventory cost money as does the ordering process. A model called Economic Order Quantity (EOQ) strives to minimize the holding and ordering costs. Some of these costs are obvious, others are not. The Japanese engineer, Shigeo Shingo, has pointed out that if the ordering cost could be reduced to near zero, it would be economic to make items to order. He proposes that such a condition be approached by reducing the set-up costs. This in turn means to make as much of the set-up external (while productive activities are going on) as possible. This paper discusses the EOQ model and Shingo’s concept which he calls SMED (Single Minute Exchange of Dies).
|Notes on Six Sigma Theory||
When the theory of six sigma was originally proposed was based on a wrong interpretation of control chart theory. The concept of the six-sigma has since evolved to be a catch phrase for continual improvement. While this is good, some vestiges of the original theory still float about. This paper examines the original theory and explains why it was incorrect and why following the original concept could lead to costs much larger than necessary.
|The Sigma Enigma||
Since many managers studied statistics a long time ago, the concept of sigma is explained in this paper. The concept of the Normal curve is discussed and numbers are presented to show what is meant by six-sigma in context of a Normal Curve.
|t-Charts||When measuring an attribute such as whether an error was made or not made, we often plot a the percentage of errors on a control chart called a p-chart. This chart is dependent on the number of measurement used for each data point or observation. When these measurements differ greatly from one observation to the next, the control limits vary making the chart difficult to interpret. The method of t-charts transposes the data to result in a new chart with stable limits while maintaining the patterns of the p-chart.|
|Which Path to Quality?||
There are many different systems in vogue today that claim to be the final word in achieving quality. Using a taxonomy of
|The Executive's Guide to Process Control||This is a draft of a book about process control. At this time it requires a password to access the pdf files. Contact me Latzko@att.net if you are interested in reviewing this draft.|
|This is Dr. Latzko's Dissertation|
|The Underutilized Control Chart||
Since 1924, when Dr. Walter A. Shewhart devised the control chart, the control of quality changed dramatically. With time the emphasis has shifted from statistical thinking, as represented by the control chart, to procedures and problem solving. This paper reviews some issues related to control charts. Using service and manufacturing examples show the power of this tool.
Control charts are one method that started the modern quality control profession. Their use is still valid today. This article shows, by example, how the control chart can be used in areas other than manufacturing. Unfortunately, few uses are made of control charts in service applications. The text argues that particularly those ASQ members engaged in service activities can gain great insights by making more use of this tool.
This thesis also argues that part of the reason for the low use of control charts lies in the misconceptions surrounding the methods. Some of these misconceptions are examined and discussed.
|The Control Chart as a Diagnostic Tool||
Many people know that the control chart is a tool that distinguishes special causes from common causes of variation. In essence, that is all that it does. The use of this tool is not as frequent as one might expect. In most instances it seems to be used to maintain a process at a reasonable level. This paper discusses the use of the control chart as a test instrument. Five examples are presented as well as some background from the theory of control charts.
|Enhanced Management Reports||Management reporting is of relatively recent origin. Financial reporting such as bookkeeping and accounting has been around much longer. Because of this, it is not surprising that managers adopted financial reporting method to get the information for managerial control. Such methods, however, were not designed for managerial control. A tool invented for process quality performance measurement, the Process Control Chart, is ideal for giving managers maximum information at minimum cost. Examples contrasting usual management reports with the Process Chart are presented.|
|Quality Issues in the US||This is an Adobe Portable Document Format (PDF) file of a slide presentation given to the New Jersey Pharmaceutical Quality Control Association. It requires the use of the free Adobe Acrobat Reader.|
|Chapter_10_Section_7||This is a sample of my lecture at Fordham|
|A Practical Way to Maintain Quality||
Many books discuss the mechanics of initially setting up a method for measuring processes often called Statistical Process Control (SPC). A number of these books show how to identify special causes of variation that impact the process quality. Often, advice is presented of how to improve the process once special causes are identified. Some of the books also discuss important issues such as rational sub-grouping. However, few texts discuss what Shewhart called "control charts as an operation" once the special causes are identified and acted upon.
|Manage Knowledge Workers for Lean Process Quality (QUIP)||This paper deals with how one can measure the quality of knowledge workers (clerks, doctors, managers, etc.). Errors made in knowledge work are wasteful (anti-lean) and, often, very costly. This paper shows how to determine when the errors of knowledge workers are beyond what one expects from the system, the system capability. Moreover, it shows what to do about such a situation. It is an nf the QUIP (Quality Improvement Program).|