4.1 RFID equipment set-up for data capturing
RFID technology is adopted to collect real-time data, and to
monitor the real-time inventory status and physical storage
conditions in the warehouse. This helps to enhance the
information flow, visualize the instantaneous warehouse
operations process, and facilitate decision making in
operations assignment and monitoring. It is the basis for
providing the data for the other two modules. RFID
equipment such as readers and antennas are set in the
warehouse to capture real-time operations data. On the other
hand, passive tags are attached to the incoming products and
the warehouse facilities, including material handling
equipment and workstations. When the tags receive the radio
signal emitted by the reader, the information stored in the tag
will be reflected to the readers. Once the reader receives the
information from the tags, the data will be stored in the
centralized database after decoding from the middleware.
4.2 Data collection through interviews with warehouse
representatives
In order to have better understanding about the current
situation in the warehouse, interviews with warehouse
representatives of ABC Manufacturing Co. Ltd. are
conducted. A set of questions related to its warehouse
operations, including major warehouse and production
activities, processing, resources usage and managerial
problems as well as possible risks, cause of the risks and
solutions, are prepared for warehouse representatives. The
potential risks are divided into 9 categories which are
resource risk, operations risk, physical environment risk,
human risk, managerial risk, financial risk, market risk,
regulatory/policy risk and security risk according to the
warehouse situation and customer order specifications. This
provides flexibility to the customer which can also limit the
time and effort paid in comparison. Hence, there is a practical
need to go through the steps of the AHP model in order to
figure out the major types of risks of concern to customers.
4.3 Hierarchy modeling of potential risk factors
The potential risk factors are then categorized in the
hierarchical structure. To determine the importance of the
risk factor, three levels of the hierarchical model are built, the
goal, criteria and alternatives. On the other hand, to
determine the importance of sub-risk factors, four levels of
the hierarchical model are built, includes the goal, criteria,
attributes and alternatives. In the three levels of the hierarchy,
as it is difficult to evaluate the risk likelihood, without any
specific details of the risk and the description of the risk
factor is extensive, only consequence/severity are considered
as criteria to estimate the impacts. In the four level hierarchy,
both the likelihood and consequence/severity are considered
as criteria because the likelihood of sub-risk factors can be
evaluated with detailed descriptions. In addition, to quantify
the degree of consequence/severity, 8 criteria are defined:
cost, efficiency, productivity, time wasting, quality,
reputation, financial loss and interruption. The likelihood of
occurrence is then quantified by frequency, persistence and
ability to control.
4.4 Pair-wise comparison and priority synthesis
Pair-wise comparison is then conducted to compare each
alternative based on the criteria of likelihood and
consequence/severity. For each risk factor, the importance is
determined by the rating given for two criteria in pairs. As a
result, the importance of the risk factor and sub-risk factor is
compared and ranked according to the priority vector. Fig. 3
shows the 3-level hierarchical structure for determining the
importance of the risk factors. The 8 criteria, including cost,
efficiency, productivity, time wasting, quality, reputation,
financial loss and interruption are defined to determine the
type of risk of the highest concern. The results show that
operations risk has the highest average weight of 23%.
Therefore, only the importance of sub-risk factors for
operations risk is considered and ranked according to the
calculated priority vector. Among all identified sub-factors,
power failure has the highest average weight of 15%;
followed by the risk in cargo delivery with average weight of
14.5% and miscommunication with average weight of 11.9%,
as shown in Fig. 4. The risk with the highest importance level
is included as an input parameter of CBR to formulate the
logistics workflow.