This paper provides preliminary discourse on buzz words about Industry 4.0 and Society 5.0. This discourse focuses on the lens of Condition Based Maintenance (CBM) and Machine Learning of Artificial Intelligence (MLAI). To some extent several companies have embarked Industry 4.0 and Society 5.0 within Internet of Things (IoT) technology. Through the wave of IoT Technology, Industries are adopting automated machinery. Predictive maintenance (PM) is indispensable not only toward the machines” vitality and longevity purpose, but also toward the human error reduction. This paper elaborates its discourse of Industry 4.0 and Society through the lens of CBM and MLAI. The mentioned Machine Learning, in this paper, refers to research methodology, as methodological frameworks. Those frameworks comprise several phases, which are: 1. Equipment Analysis; 2. Data Evaluation; 3. Data Selection and Process; 4. Modeling; 5. Decision Support Model Evaluation. The MLAI techniques are based upon the identification of behaviour patterns. This identification comprises datasets that exclude mathematical models or prior historical knowledge. The discourse in this paper intertwines CBM process and MLAI through data cleaning and processing, features stratification and extraction, model stratification and validation. This paper elaborates two renowned maintenance approaches which are preventive and corrective maintenance. Discourse in this paper focuses on corrective action, known as predictive maintenance (PM), or condition based maintenance (CBM) within Reliability Centered Maintenance (RCM). CBM is chosen as the most desirable strategy, as it involves the intervention as the consequence of the machine breakdown. It also provides cost savings toward spare parts consumption, and optimizes production.

One of the important activities to achieve a sustainable palm oil company is by improving the sustainable supply chain management, especially being in line with the lean and green SCM concepts. The lean concept aims to reduce costs and to increase the effectiveness of the supply chain. While the green concept tries to ensure that the ongoing process keeps bringing good effect on the environment. In designing the performance measurement of the sustainable supply chain through the lean & green supply chain management approach, this study includes a formulation for Key Performance Indicators (KPI) and grouping of the lean and green indicators which are integrated with the balanced scorecard (BSC) perspectives. It obtained 28 KPIs which consists of 15 lean supply chain KPIs and 13 green supply chain KPIs. Based on overall weighting, the highest priority KPI is the company’s total revenue and total operating costs, followed by the total cost of the supply chain (all of them are from a financial perspective). The weights of three KPIs are 0.103, 0.078 and 0.072 respectively.

This paper conveys the theoretical perspectives of sustainable industrial systems through Strategic Laboratory Equipment Industry, within scope of PT. Promedika Sejahtera (PPS). PT Promedika Sejahtera is a company engaged in the laboratory equipment industry, that need its strategic touch on its Strategic Laboratory Equipment. Products sold by the company are Oxygen, Medical Equipment, Ultraviolet System, Activated Carbon Filter, Pempers, and Underpad. Products that exist in the company are not in their own production in the production from abroad. PT Promedika Sejahtera merely sell the laboratory equipment. Yet, the company has various types of consumers namely hospitals, hospital cooperatives, pharmacies, factories, and water equipment RO shops. In this paper, strategic laboratory equipment industry refers specifically to inventory within the supply chain management perspectives. This paper constitutes collaboration with other papers on Economic Order Quantity (EOQ), Re-Order Point (ROP), and Safety Stock (SS), that convolutes Forecasting, ABC Analysis, and Partial Least Square (PLS). Yet, this paper refers to its focus merely on Forecasting, Demand Pattern, Exponential Smoothing and EOQ. As part of conclusion, this paper conveys several highlighted remarks. Those remarks refer to ABC Analysis. The grouping of goods using ABC Analysis Method is divided into three groups: A with 80% priority, group B with 20% priority and group C with 10% priority. The number of goods in group A is 12 items, group B 18 item type and group C are 30 items of goods. Forecasting demand required by the Company for 2018 based on priority group A can be done using the Double Exponential Smoothing (Holt’s) Method because the pattern pattern possessed from the previous year’s sales data has no seasonal but has a random trend. The results of these calculations can be seen from the table of existing research results. Ultimately, Future research is deemed indispensable within novelty purpose for the industrial system sustainability within Strategic Laboratory Equipment Industry.

Company shall give full attention to the quality of the products. In the electronics industry, quality control is the key to gain the loyalty of the customer. This is the basis for making improvement at the production activities, especially in controlling the quality in order to reduce the problem of scratch on the cover bottom using the six sigma DMAIC method. The purpose of this research is to analyze the factor that will cause defect to the product. The aimed target is to reduce the lower problem of defective products cover bottom 50%, it also to get the best result where previous defective products amounted to 8183 ppm has downed to 291 ppm and the level of the previous sigma 3,89σ rose to 4,94σ, the target is 4,14σ. This was result an exceed achievement from the Company’s target more than 50%. Six Sigma is the most effective tools at the present time, this will affect to eliminate defects, cut the time of making the product, eliminate unnecessary costs and the principal concept of science to support the sustainability of business which is focused on improving quality and customer satisfaction. The key success of improving quality depends on the ability to identify and solve the problems. This application may be useful and align with the company's philosophy, so that it can be expected to get the final outcome of the company.

This paper combined both theoretical perspective of Lean Six Sigma and Business Engineering; and its managerial implementation within electrical energy company in Middle East. The mentioned company is producing nitrogen gas for the supply purpose of oil, chemical and manufacturing industry processes. Integrative part of this company’s strategic objectives refers to profitability improvement and production performance through escalating company profit. In narrowed down objective scope, it refers to the Electrical Energy Optimization. This paper relates the mentioned company’s empirical and managerial implementation with theoretical perspective of Lean Six Sigma and Business Engineering. Quantitative approach of Lean Six Sigma and Six Sigma are capitalized in this paper’s research methodology to identify problem cause. This paper in particular elaborates the scholar view of Hadid et al (2016) on Lean Six Sigma. The mentioned scholar views within theoretical perspective. It investigates the interaction term between Lean’s social practices and technical practices against the performance measures of financial and operations. This investigation relates to the company’s strategic objectives as unit analysis in this paper. Furthermore, the scholar view of Bärenfänger and Steinbuß (2015) view Business Engineering in its Digital form of Business Engineering as a comprehensive method for digital business model design. Subsequently, data results in this paper convey its interpretation results from production division, which is approximately 81.16% of nitrogen gas that is originated from engine design as its problem cause. To conclude, within Lean Six Sigma and Six Sigma, this paper discussion refers to the value of 1.36 that becomes 2.62 ratio. Specific power of production decreases from 1.45 kw/Nm3 into 0.646 kw/Nm3, as originated from the escalating production of the so called highly impact the company performance versus costs incurred.Ultimately, it is harnessing discussion of the theoretical and managerial implication in this paper.