Performance Assurance for Smart Manufacturing Systems

SUBMITTED BY: RANJAN KUMAR PATEL Reg. No. PG/MSE/136011

UNDER THE GUIDANCE OF: Mr. AMRIK SINGH DR. JATINDER MADAN (Associate Professor) (Associate professor)

DEPARTMENT OF MECHANICAL ENGINEERING SANT LONGOWAL INSTITUTE OF ENGINEERING AND TECHNOLOGY (Deemed-to-be-University), LONGOWAL, SANGRUR-148106(PUNJAB)

To develop KPI and assessment methods to implement smart manufacturing in SME

CONTENT Introduction Literature review Problem formulation Research methodology ObjectivesReferencesINTRODUCTION TO KPI

KPIs are assorted variables that organizations use to assess, analyze and track manufacturing processes.

These performance measurements are commonly used to evaluate success in relation to goals .

KPIs tend to vary by organization to organization and industry to industry.Seven most important kpi in manufacturing sector

Count(Good or Bad)Reject ratioRate TargetTakt Time(Cycle time)Overall Equipment RatioDown TimeDefining KPIs

SpecificMeasurableAchievableResult orientedTime boundLiterature Review Requirements and Prerequisites of metricsIn a first step general requirements of KPI are summarized to provide a solid knowledge base for the development of the necessary KPIs . Levinson and Rerick (Levinson and Rerick, 2002) define three standards for appropriate performance measurements: 1 Measurement should be objective, could be precisely defined, and could be measurable with numbers.2. Performance should be controlled by people or department that is measured.3. The performance measurement must help the company to meet its goal.CONTD: Maskell (Maskell, 1991) postulates the following characteristics for a performance measurement system in a world class manufacturing enterprise:

They are intended to foster improvement rather than simply monitor performance.

They change over time as needs change.

They are simple and easy to use.

They provide fast feedback to operators and managers

CONTDAccording to Lind (Lind, 2001) who conducted a case study to understand the financial and non-financial measures of a World Class Manufacturing company revealed that non-financial measures were used for the day-to-day control, whereas financial measures were used for long-term control .

Neely et al. (Neely, 1994) regard performance measurement as the quantification of the effectiveness and/or efficiency of an activity over a given time period.Problem FormulationThere is lack of integration among KPI and other assessment method so that it always produce results which help plant to achieve their objectives.

There is no specific model which show effect of other KPI if it had been chosen.

To produce KPI reports manually requires considerable time. It is often the department managers who face the never-ending task of compiling their key performance indicators and producing reports accordingly.

RESEARCH METHODOLOGY REGRESSION ANALYSIS entails analysis of a sequence of measurements made at specified time intervals.

Smoothing method uses the averaging methods and exponential smoothing methods to reveal clearly the underlying trend, seasonal and cyclic components from data sets.

Linear programming the types of models that can be used are the descriptive mathematical models and simulation models.CONTD:

Excel model The modern trend in programming applications is graphical interfaces. This means that the user interacts with a program through a graphical interface e.g. values are entered in text boxes, options are selected from graphical menus and answers are presented graphically.

Incuity a software based program in which metric prepare in the form user friendly excel sheet and graphs.Objectives The thesis will focus on the problem of performance assurance from multiple directions:Identify the unique characteristics of KPI for performance issues for SMS.

Determine the measures of performance for SMS (i.e., the metrics).

Develop methods for interpreting metrics in terms of the KPIs for SMS.

Identify approaches to address performance deviation.

What is the new technical ideaOne of the fundamental requirements for Smart Manufacturing Systems is that they are able to rapidly respond to situational changes with an acceptable level of performance. To fundamental measurement science challenges for meeting this requirement are to recognize changes in performance through the use of performance measures and to define those measures in such a way that performance problems can be traced to the source. Finally, understanding correlations between performance measures, as well as accuracy of the measures, can be used to establish an acceptable system performance .ReferencesSMEs. Journal of Manufacturing Technology Management, Vol. 17, 460-471.AHLSTROEM, P. & KARLSSON, C. (1996) Change processes towards lean production: The role of the managementaccounting system. International Journal of Operations & Production Management,, Vol. 16, 42-56.BOURNE, K., MILLS, J., WILCOX, M., NEELY, A., PLATTS, K. (2000) Designing, implementing and updating performance measurement system. International Journal of operations management, 20, 754-771.CARTON, R. B. (2006) Measuring organizational performance : metrics for entrepreneurship and strategic management