Dr Koh Niak Wu is the Founder and CEO of Cosmiqo International Pte Ltd, a company that is focused on building intelligent systems that optimises resource allocation for 4-wall operations. He specialises in supply chain analytics, strategy execution and operations management innovation. He is an Intellectual Transcendences 2019 recipient recognised by the Asian Productivity Organisation and China Productivity Centre.
Dr Koh was formerly part of the Global Supply Chain and Logistics team at Dell contributing to strategy analytics. He was also in the Planning and Operations Management Group at SIMTech, A*STAR where he gained valuable insights into the evolution of industries. Additionally, Dr Koh is an Adjunct Faculty at the Singapore Management University (SMU) and Singapore University of Social Sciences where he shares his views and cross-industry experiences on supply chains and operations management. He is also an Expert with the Asian Productivity Organisation (APO) and has been sharing his views on the future economy across Asia and the Pacific.
Dr Koh codes, believes in the power of operational analytics and how it shapes business decisions. He holds a Doctor of Philosophy in Robotics from the National University of Singapore and a Bachelor of Engineering (Double 1st) from King's College London.
With increasing demand and shorter fulfilment times for orders across different industries, the need to fill these orders more efficiently through optimal manpower optimisation and increased picking efficiency in warehouses is thus necessary. A cloud-based/on-premise computing solution was designed for pick-path optimisation that aims to optimise the least efficient and mostly costly part of the order fulfilment process. This improves efficiency of pickers' routes within 4 walls of a warehouse, allowing for close to 17-34% increased efficiency or less time spent on similar picking operations, allowing increased number of picks with the current capacity of the picking operations. More picks with the same manpower means faster fulfilment times and more revenue generated with the same resources.
An on-going challenge is the lagging indicators and paper trails resulting from manufacturing-related data. This translates into losses that could have been avoided if only more up-to-date information was available. This work evolved into a real-time visibility and predictive analytics engine by retro-fitting manufacturing operations with sensor-based platforms. The collection of valuable manufacturing-related data can be analysed to amplify and streamline company operations. Powered by an intelligent sensor network, the insights generated from both data collection and analytics allows users to simplify the manufacturing operations decision making process and achieve optimal throughput efficiency. As a result, leading indicators are obtained contributing towards a firm's competitiveness.
Manufacturing
Logistics
Manufacturing
Materials
Manufacturing
Infocomm
Electronics
Chemicals
Manufacturing
Chemicals
Environment
Infocomm
Electronics
Materials
Energy
Foods
Manufacturing